saim1212 commited on
Commit
f0456cd
·
verified ·
1 Parent(s): 2fa44d9

second model upload

Browse files
README.md CHANGED
@@ -36,18 +36,18 @@ More information needed
36
 
37
  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
39
- - train_batch_size: 2
40
  - eval_batch_size: 8
41
  - seed: 42
42
  - distributed_type: multi-GPU
43
  - num_devices: 2
44
- - gradient_accumulation_steps: 2
45
- - total_train_batch_size: 8
46
  - total_eval_batch_size: 16
47
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
48
  - lr_scheduler_type: cosine
49
  - lr_scheduler_warmup_ratio: 0.1
50
- - num_epochs: 25.0
51
  - mixed_precision_training: Native AMP
52
 
53
  ### Training results
 
36
 
37
  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
39
+ - train_batch_size: 4
40
  - eval_batch_size: 8
41
  - seed: 42
42
  - distributed_type: multi-GPU
43
  - num_devices: 2
44
+ - gradient_accumulation_steps: 4
45
+ - total_train_batch_size: 32
46
  - total_eval_batch_size: 16
47
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
48
  - lr_scheduler_type: cosine
49
  - lr_scheduler_warmup_ratio: 0.1
50
+ - num_epochs: 15.0
51
  - mixed_precision_training: Native AMP
52
 
53
  ### Training results
adapter_config.json CHANGED
@@ -20,442 +20,314 @@
20
  "rank_pattern": {},
21
  "revision": null,
22
  "target_modules": [
23
- "model.layers.26.self_attn.o_proj",
24
- "model.layers.19.self_attn.o_proj",
25
- "visual.blocks.22.mlp.fc1",
 
 
 
 
 
 
26
  "model.layers.1.self_attn.o_proj",
27
- "model.layers.9.mlp.up_proj",
28
- "model.layers.23.self_attn_text.q_proj",
29
- "model.layers.24.self_attn_text.o_proj",
30
- "model.layers.15.self_attn_text.o_proj",
31
- "model.layers.27.self_attn.v_proj",
32
- "model.layers.8.self_attn_text.k_proj",
33
- "visual.blocks.10.attn.proj",
34
- "visual.blocks.28.mlp.fc2",
35
  "model.layers.3.self_attn_text.k_proj",
36
- "model.layers.12.self_attn.v_proj",
37
- "model.layers.18.self_attn_text.o_proj",
38
- "visual.blocks.5.mlp.fc2",
39
- "model.layers.13.self_attn.q_proj",
40
- "visual.blocks.7.mlp.fc1",
41
- "model.layers.27.mlp.down_proj",
42
- "visual.blocks.1.mlp.fc1",
43
- "model.layers.12.mlp.up_proj",
44
- "model.layers.5.self_attn.o_proj",
45
- "model.layers.15.self_attn_text.q_proj",
46
- "model.layers.2.self_attn_text.k_proj",
47
- "model.layers.3.self_attn_text.q_proj",
48
- "model.layers.12.mlp.down_proj",
49
- "model.layers.14.self_attn_text.q_proj",
50
- "model.layers.19.self_attn_text.o_proj",
51
- "visual.blocks.23.attn.proj",
52
- "model.layers.20.self_attn.o_proj",
53
- "model.layers.5.self_attn_text.k_proj",
54
- "model.layers.26.mlp.gate_proj",
55
- "model.layers.8.self_attn.q_proj",
56
- "model.layers.20.mlp.gate_proj",
57
- "model.layers.16.self_attn_text.k_proj",
58
  "model.layers.20.self_attn.k_proj",
59
- "visual.blocks.9.attn.qkv",
60
- "model.layers.4.self_attn_text.k_proj",
61
- "model.layers.4.mlp.gate_proj",
62
- "model.layers.6.self_attn.v_proj",
63
- "model.layers.1.self_attn_text.o_proj",
64
- "model.layers.16.mlp.up_proj",
65
- "visual.blocks.16.mlp.fc2",
66
- "model.layers.10.self_attn.v_proj",
67
- "model.layers.17.self_attn_text.o_proj",
68
- "model.layers.17.self_attn.v_proj",
69
- "visual.blocks.9.mlp.fc1",
70
- "model.layers.25.mlp.gate_proj",
71
- "model.layers.25.self_attn_text.q_proj",
72
- "model.layers.9.self_attn.k_proj",
73
- "model.layers.18.self_attn.q_proj",
74
- "visual.blocks.9.attn.proj",
75
- "visual.blocks.14.mlp.fc1",
76
- "model.layers.13.self_attn.o_proj",
77
- "model.layers.24.self_attn.v_proj",
78
- "model.layers.11.mlp.down_proj",
79
- "model.layers.27.self_attn_text.v_proj",
80
- "model.layers.16.self_attn_text.o_proj",
81
- "model.layers.25.mlp.down_proj",
82
- "visual.blocks.4.mlp.fc2",
83
- "model.layers.27.self_attn.q_proj",
84
- "visual.blocks.5.attn.proj",
85
  "model.layers.19.mlp.gate_proj",
86
- "model.layers.14.self_attn.o_proj",
87
- "model.layers.19.self_attn.v_proj",
88
- "model.layers.13.mlp.gate_proj",
89
- "model.layers.18.self_attn.o_proj",
90
  "model.layers.18.self_attn.k_proj",
91
- "model.layers.26.self_attn.k_proj",
92
- "model.layers.9.self_attn_text.o_proj",
93
- "model.layers.26.self_attn.v_proj",
94
- "model.layers.27.self_attn.k_proj",
95
- "model.layers.25.self_attn.o_proj",
96
- "visual.blocks.20.attn.proj",
97
- "visual.blocks.26.attn.qkv",
98
- "model.layers.23.self_attn_text.v_proj",
99
- "visual.blocks.14.attn.qkv",
100
- "model.layers.19.self_attn.k_proj",
101
  "model.layers.13.self_attn_text.q_proj",
102
- "model.layers.13.mlp.down_proj",
103
- "model.layers.21.self_attn.k_proj",
104
- "model.layers.0.self_attn_text.o_proj",
105
- "model.layers.6.self_attn.k_proj",
106
- "visual.blocks.31.attn.proj",
107
- "model.layers.16.self_attn.v_proj",
108
- "model.layers.20.mlp.up_proj",
109
- "visual.blocks.3.mlp.fc2",
110
- "model.layers.3.self_attn.k_proj",
111
- "visual.blocks.12.attn.qkv",
112
- "model.layers.10.self_attn.k_proj",
113
- "model.layers.12.self_attn_text.k_proj",
114
- "visual.blocks.22.mlp.fc2",
 
 
 
115
  "model.layers.11.self_attn.q_proj",
116
- "visual.blocks.19.mlp.fc1",
117
- "visual.blocks.2.mlp.fc1",
118
- "model.layers.26.self_attn_text.k_proj",
119
- "model.layers.5.self_attn.q_proj",
120
- "model.layers.7.self_attn.q_proj",
121
- "visual.blocks.27.attn.proj",
122
  "model.layers.8.self_attn_text.v_proj",
123
- "model.layers.12.mlp.gate_proj",
124
- "model.layers.27.self_attn_text.q_proj",
125
- "visual.blocks.1.attn.proj",
126
- "model.layers.4.self_attn_text.o_proj",
127
- "visual.blocks.6.mlp.fc2",
128
- "model.layers.26.self_attn_text.v_proj",
129
- "visual.blocks.6.mlp.fc1",
130
- "visual.blocks.31.mlp.fc1",
131
- "model.layers.8.mlp.gate_proj",
132
- "visual.blocks.18.mlp.fc1",
133
- "visual.blocks.14.attn.proj",
134
- "model.layers.15.self_attn.o_proj",
135
- "model.layers.16.self_attn.q_proj",
136
- "visual.blocks.7.mlp.fc2",
137
- "model.layers.11.self_attn.k_proj",
138
- "model.layers.7.mlp.up_proj",
139
- "model.layers.10.self_attn_text.v_proj",
140
- "model.layers.23.self_attn.k_proj",
141
- "visual.blocks.11.attn.qkv",
142
- "visual.blocks.5.attn.qkv",
143
- "model.layers.15.self_attn_text.v_proj",
144
- "visual.blocks.21.attn.proj",
145
- "model.layers.10.mlp.gate_proj",
146
- "model.layers.5.self_attn.v_proj",
147
- "model.layers.6.mlp.down_proj",
148
- "model.layers.9.self_attn_text.v_proj",
149
- "model.layers.4.self_attn_text.q_proj",
150
- "model.layers.21.self_attn.v_proj",
151
- "model.layers.8.mlp.down_proj",
152
- "visual.blocks.8.mlp.fc2",
153
- "model.layers.23.self_attn_text.o_proj",
154
- "model.layers.1.self_attn.q_proj",
155
- "model.layers.20.self_attn_text.k_proj",
156
- "model.layers.8.self_attn.o_proj",
157
- "model.layers.20.self_attn_text.o_proj",
158
- "model.layers.6.mlp.up_proj",
159
- "model.layers.1.mlp.down_proj",
160
- "model.layers.18.mlp.down_proj",
161
- "model.layers.18.mlp.gate_proj",
162
- "model.layers.11.mlp.up_proj",
163
- "visual.blocks.2.attn.proj",
164
- "model.layers.0.mlp.down_proj",
165
- "visual.blocks.0.mlp.fc2",
166
- "visual.blocks.25.attn.proj",
167
- "model.layers.0.self_attn.k_proj",
168
- "model.layers.27.self_attn_text.k_proj",
169
- "visual.blocks.12.mlp.fc1",
170
- "model.layers.9.self_attn.q_proj",
171
- "visual.blocks.17.attn.qkv",
172
- "model.layers.17.self_attn_text.q_proj",
173
- "model.layers.15.mlp.gate_proj",
174
- "visual.blocks.21.attn.qkv",
175
- "model.layers.16.mlp.gate_proj",
176
- "model.layers.19.self_attn_text.v_proj",
177
- "model.layers.24.self_attn_text.q_proj",
178
- "visual.blocks.8.mlp.fc1",
179
- "visual.blocks.30.mlp.fc2",
180
- "model.layers.10.self_attn.q_proj",
181
- "model.layers.14.mlp.gate_proj",
182
- "model.layers.5.self_attn_text.q_proj",
183
- "visual.blocks.26.mlp.fc2",
184
- "model.layers.1.self_attn_text.k_proj",
185
- "visual.blocks.29.mlp.fc1",
186
- "model.layers.18.self_attn.v_proj",
187
- "model.layers.23.mlp.gate_proj",
188
- "visual.blocks.13.mlp.fc1",
189
- "model.layers.5.self_attn_text.o_proj",
190
- "model.layers.14.mlp.up_proj",
191
- "visual.blocks.6.attn.qkv",
192
- "model.layers.23.mlp.up_proj",
193
- "model.layers.14.self_attn_text.v_proj",
194
- "visual.blocks.4.mlp.fc1",
195
- "visual.blocks.20.attn.qkv",
196
- "model.layers.6.self_attn_text.q_proj",
197
- "visual.blocks.25.attn.qkv",
198
- "visual.blocks.15.attn.qkv",
199
- "model.layers.1.self_attn.k_proj",
200
- "model.layers.19.self_attn.q_proj",
201
- "model.layers.4.self_attn.o_proj",
202
- "model.layers.8.self_attn.v_proj",
203
- "visual.blocks.23.attn.qkv",
204
- "model.layers.3.self_attn.q_proj",
205
- "model.layers.5.mlp.gate_proj",
206
- "model.layers.1.mlp.up_proj",
207
- "model.layers.11.mlp.gate_proj",
208
- "visual.blocks.24.mlp.fc2",
209
- "model.layers.1.mlp.gate_proj",
210
- "visual.blocks.20.mlp.fc1",
211
- "visual.blocks.13.mlp.fc2",
212
- "visual.blocks.14.mlp.fc2",
213
- "visual.blocks.3.attn.qkv",
214
  "model.layers.12.self_attn_text.q_proj",
215
- "model.layers.25.self_attn_text.o_proj",
216
- "visual.blocks.19.attn.proj",
217
- "visual.blocks.23.mlp.fc1",
 
 
 
 
 
 
218
  "model.layers.14.mlp.down_proj",
219
- "visual.blocks.25.mlp.fc2",
220
- "model.layers.0.self_attn_text.q_proj",
221
- "model.layers.23.self_attn_text.k_proj",
222
- "model.layers.12.self_attn.k_proj",
223
- "model.layers.4.self_attn.k_proj",
224
- "visual.blocks.28.mlp.fc1",
225
- "model.layers.21.self_attn_text.v_proj",
226
- "model.layers.10.mlp.down_proj",
227
- "visual.blocks.18.attn.qkv",
228
- "model.layers.5.mlp.up_proj",
229
- "model.layers.23.self_attn.v_proj",
230
- "visual.blocks.31.mlp.fc2",
231
- "model.layers.3.mlp.down_proj",
232
- "visual.blocks.2.mlp.fc2",
233
- "visual.blocks.10.mlp.fc2",
234
- "model.layers.27.self_attn.o_proj",
235
- "model.layers.11.self_attn_text.v_proj",
236
- "model.layers.17.self_attn_text.k_proj",
237
- "visual.blocks.25.mlp.fc1",
238
- "visual.blocks.3.attn.proj",
239
- "model.layers.2.self_attn.q_proj",
240
- "model.layers.26.self_attn_text.o_proj",
 
 
 
 
 
 
 
 
 
241
  "model.layers.9.self_attn.v_proj",
242
- "model.layers.7.self_attn_text.o_proj",
243
- "model.layers.20.self_attn.q_proj",
244
- "model.layers.21.mlp.down_proj",
245
  "model.layers.17.self_attn.q_proj",
246
- "visual.blocks.17.attn.proj",
247
- "model.layers.7.mlp.down_proj",
248
- "model.layers.21.mlp.gate_proj",
249
- "model.layers.20.mlp.down_proj",
250
- "model.layers.7.self_attn.o_proj",
251
- "model.layers.6.self_attn_text.o_proj",
252
- "model.layers.5.self_attn_text.v_proj",
253
- "model.layers.22.mlp.gate_proj",
254
- "model.layers.7.self_attn_text.k_proj",
255
- "model.layers.19.mlp.down_proj",
256
- "model.layers.6.self_attn_text.k_proj",
257
- "model.layers.9.self_attn_text.k_proj",
258
- "visual.blocks.15.attn.proj",
259
- "visual.blocks.6.attn.proj",
260
- "model.layers.22.self_attn.k_proj",
261
- "visual.blocks.13.attn.proj",
262
- "model.layers.0.mlp.gate_proj",
263
- "model.layers.13.self_attn.v_proj",
264
- "model.layers.22.self_attn.q_proj",
265
- "model.layers.19.self_attn_text.k_proj",
266
  "model.layers.10.self_attn_text.q_proj",
267
- "model.layers.2.mlp.down_proj",
268
- "visual.blocks.10.attn.qkv",
269
- "model.layers.4.mlp.up_proj",
270
- "visual.blocks.16.attn.qkv",
 
 
 
 
 
 
 
 
 
271
  "model.layers.13.self_attn_text.o_proj",
272
- "model.layers.21.self_attn.o_proj",
273
- "model.layers.13.mlp.up_proj",
274
- "model.layers.7.self_attn_text.q_proj",
275
- "visual.blocks.0.attn.proj",
276
- "visual.blocks.17.mlp.fc1",
277
- "model.layers.25.self_attn_text.v_proj",
278
- "model.layers.3.self_attn.o_proj",
279
- "visual.blocks.30.attn.proj",
280
- "model.layers.16.self_attn.o_proj",
281
- "model.layers.23.self_attn.o_proj",
282
- "model.layers.4.mlp.down_proj",
283
- "model.layers.17.self_attn_text.v_proj",
284
- "model.layers.12.self_attn.q_proj",
285
- "visual.blocks.3.mlp.fc1",
286
- "visual.blocks.26.attn.proj",
287
- "model.layers.21.self_attn.q_proj",
288
- "visual.blocks.27.attn.qkv",
289
- "model.layers.17.mlp.gate_proj",
290
- "model.layers.23.mlp.down_proj",
291
- "visual.blocks.18.mlp.fc2",
292
- "model.layers.2.self_attn.k_proj",
293
- "model.layers.9.mlp.down_proj",
 
 
 
294
  "model.layers.6.mlp.gate_proj",
295
- "visual.blocks.17.mlp.fc2",
296
- "model.layers.0.self_attn.v_proj",
297
- "visual.blocks.30.attn.qkv",
298
- "model.layers.3.self_attn_text.o_proj",
299
- "visual.blocks.4.attn.qkv",
 
 
 
 
300
  "model.layers.10.mlp.up_proj",
301
- "model.layers.2.self_attn.v_proj",
302
- "visual.blocks.5.mlp.fc1",
303
- "model.layers.0.self_attn_text.k_proj",
304
- "model.layers.25.self_attn_text.k_proj",
305
- "visual.blocks.19.attn.qkv",
306
- "model.layers.2.mlp.gate_proj",
307
- "model.layers.16.self_attn_text.q_proj",
308
- "visual.blocks.0.mlp.fc1",
309
- "model.layers.3.mlp.up_proj",
310
- "visual.blocks.30.mlp.fc1",
311
- "model.layers.2.mlp.up_proj",
312
- "visual.blocks.29.attn.qkv",
313
- "model.layers.27.mlp.gate_proj",
314
- "model.layers.21.self_attn_text.o_proj",
315
- "model.layers.21.mlp.up_proj",
316
- "model.layers.1.self_attn.v_proj",
317
- "visual.blocks.29.attn.proj",
318
- "model.layers.8.self_attn_text.q_proj",
319
- "model.layers.3.self_attn_text.v_proj",
320
- "model.layers.1.self_attn_text.v_proj",
321
- "visual.blocks.21.mlp.fc2",
322
- "model.layers.3.self_attn.v_proj",
323
- "visual.blocks.4.attn.proj",
324
- "model.layers.4.self_attn.v_proj",
325
- "model.layers.7.self_attn_text.v_proj",
326
  "model.layers.22.self_attn_text.v_proj",
327
- "model.layers.20.self_attn.v_proj",
328
- "model.layers.21.self_attn_text.q_proj",
329
- "model.layers.12.self_attn.o_proj",
330
- "visual.blocks.27.mlp.fc2",
331
- "model.layers.18.self_attn_text.k_proj",
332
- "model.layers.24.self_attn_text.v_proj",
333
- "model.layers.26.mlp.up_proj",
334
- "model.layers.8.self_attn_text.o_proj",
335
- "visual.blocks.11.mlp.fc1",
336
- "model.layers.1.self_attn_text.q_proj",
337
- "model.layers.7.self_attn.v_proj",
338
- "visual.blocks.26.mlp.fc1",
339
- "model.layers.11.self_attn.v_proj",
340
- "model.layers.13.self_attn.k_proj",
341
- "model.layers.10.self_attn.o_proj",
342
- "model.layers.15.mlp.up_proj",
343
- "visual.blocks.15.mlp.fc1",
344
- "model.layers.22.mlp.down_proj",
345
- "model.layers.24.mlp.up_proj",
346
- "visual.blocks.15.mlp.fc2",
347
- "model.layers.10.self_attn_text.o_proj",
348
- "model.layers.15.self_attn_text.k_proj",
349
- "visual.blocks.1.attn.qkv",
350
- "model.layers.11.self_attn_text.o_proj",
351
- "visual.blocks.10.mlp.fc1",
352
  "model.layers.17.mlp.down_proj",
353
- "visual.blocks.24.attn.qkv",
354
- "model.layers.24.mlp.gate_proj",
355
- "visual.blocks.7.attn.qkv",
356
- "model.layers.5.self_attn.k_proj",
357
- "model.layers.23.self_attn.q_proj",
358
- "model.layers.0.mlp.up_proj",
359
- "model.layers.22.self_attn_text.q_proj",
360
- "visual.blocks.12.mlp.fc2",
361
- "model.layers.3.mlp.gate_proj",
362
  "model.layers.18.self_attn_text.v_proj",
363
- "model.layers.12.self_attn_text.o_proj",
364
- "model.layers.5.mlp.down_proj",
365
- "model.layers.10.self_attn_text.k_proj",
366
- "visual.blocks.24.attn.proj",
367
- "model.layers.11.self_attn_text.q_proj",
368
- "model.layers.25.self_attn.v_proj",
369
- "model.layers.17.mlp.up_proj",
370
- "visual.blocks.23.mlp.fc2",
371
  "model.layers.22.self_attn.o_proj",
372
- "model.layers.14.self_attn_text.o_proj",
373
- "model.layers.19.mlp.up_proj",
374
- "model.layers.14.self_attn.k_proj",
375
- "visual.blocks.31.attn.qkv",
376
- "model.layers.13.self_attn_text.v_proj",
377
- "model.layers.16.mlp.down_proj",
378
- "model.layers.16.self_attn_text.v_proj",
379
- "model.layers.24.self_attn_text.k_proj",
380
- "model.layers.26.self_attn_text.q_proj",
381
- "visual.blocks.16.attn.proj",
382
- "visual.blocks.22.attn.qkv",
383
- "model.layers.27.self_attn_text.o_proj",
384
- "visual.blocks.27.mlp.fc1",
385
- "visual.blocks.12.attn.proj",
386
- "visual.blocks.28.attn.proj",
387
  "model.layers.21.self_attn_text.k_proj",
388
- "visual.blocks.28.attn.qkv",
389
- "visual.blocks.21.mlp.fc1",
390
- "model.layers.27.mlp.up_proj",
391
- "model.layers.15.self_attn.v_proj",
392
- "model.layers.24.self_attn.k_proj",
393
- "model.layers.2.self_attn_text.q_proj",
394
  "model.layers.15.self_attn.q_proj",
395
- "visual.blocks.29.mlp.fc2",
396
- "visual.blocks.13.attn.qkv",
397
- "visual.blocks.24.mlp.fc1",
398
- "model.layers.11.self_attn.o_proj",
399
- "model.layers.2.self_attn_text.o_proj",
400
- "visual.blocks.7.attn.proj",
401
- "model.layers.6.self_attn.o_proj",
402
- "model.layers.9.self_attn_text.q_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
403
  "model.layers.0.self_attn.o_proj",
404
- "model.layers.9.mlp.gate_proj",
405
- "visual.blocks.0.attn.qkv",
406
- "model.layers.2.self_attn_text.v_proj",
407
- "model.layers.8.mlp.up_proj",
408
- "visual.blocks.8.attn.proj",
409
- "visual.blocks.18.attn.proj",
410
  "model.layers.4.self_attn_text.v_proj",
411
- "model.layers.17.self_attn.o_proj",
412
- "visual.blocks.22.attn.proj",
413
- "model.layers.9.self_attn.o_proj",
414
- "model.layers.26.self_attn.q_proj",
415
- "visual.blocks.11.mlp.fc2",
416
- "model.layers.22.mlp.up_proj",
417
- "model.layers.18.mlp.up_proj",
 
418
  "model.layers.14.self_attn_text.k_proj",
419
- "visual.blocks.9.mlp.fc2",
420
- "visual.blocks.11.attn.proj",
421
- "model.layers.17.self_attn.k_proj",
422
- "model.layers.8.self_attn.k_proj",
423
- "model.layers.12.self_attn_text.v_proj",
424
- "model.layers.26.mlp.down_proj",
425
- "model.layers.14.self_attn.v_proj",
426
- "model.layers.22.self_attn_text.o_proj",
427
- "model.layers.0.self_attn_text.v_proj",
428
- "model.layers.7.mlp.gate_proj",
429
- "model.layers.22.self_attn.v_proj",
430
- "model.layers.24.mlp.down_proj",
431
- "model.layers.20.self_attn_text.q_proj",
432
- "model.layers.2.self_attn.o_proj",
433
- "model.layers.11.self_attn_text.k_proj",
434
- "model.layers.24.self_attn.q_proj",
435
- "model.layers.18.self_attn_text.q_proj",
436
- "model.layers.6.self_attn_text.v_proj",
437
- "model.layers.0.self_attn.q_proj",
438
- "model.layers.25.self_attn.q_proj",
439
  "model.layers.19.self_attn_text.q_proj",
440
- "visual.blocks.20.mlp.fc2",
441
- "model.layers.13.self_attn_text.k_proj",
442
- "model.layers.25.mlp.up_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
443
  "model.layers.20.self_attn_text.v_proj",
444
- "visual.blocks.8.attn.qkv",
445
- "visual.blocks.16.mlp.fc1",
446
- "model.layers.25.self_attn.k_proj",
447
- "model.layers.22.self_attn_text.k_proj",
 
 
 
 
 
 
448
  "model.layers.16.self_attn.k_proj",
 
 
 
 
449
  "model.layers.24.self_attn.o_proj",
450
- "model.layers.15.self_attn.k_proj",
451
- "visual.blocks.1.mlp.fc2",
452
- "model.layers.6.self_attn.q_proj",
453
- "model.layers.15.mlp.down_proj",
454
- "visual.blocks.2.attn.qkv",
455
- "model.layers.14.self_attn.q_proj",
456
- "model.layers.4.self_attn.q_proj",
457
- "visual.blocks.19.mlp.fc2",
458
- "model.layers.7.self_attn.k_proj"
 
 
 
 
 
 
 
 
 
 
459
  ],
460
  "task_type": "CAUSAL_LM",
461
  "use_dora": false,
 
20
  "rank_pattern": {},
21
  "revision": null,
22
  "target_modules": [
23
+ "model.layers.6.self_attn.v_proj",
24
+ "model.layers.3.self_attn.k_proj",
25
+ "model.layers.5.self_attn.k_proj",
26
+ "model.layers.20.self_attn.o_proj",
27
+ "model.layers.2.self_attn.k_proj",
28
+ "model.layers.7.self_attn_text.k_proj",
29
+ "model.layers.6.self_attn.k_proj",
30
+ "model.layers.20.self_attn.q_proj",
31
+ "model.layers.25.self_attn.q_proj",
32
  "model.layers.1.self_attn.o_proj",
33
+ "model.layers.22.self_attn.k_proj",
34
+ "model.layers.8.self_attn.k_proj",
35
+ "model.layers.18.self_attn_text.k_proj",
36
+ "model.layers.10.self_attn_text.o_proj",
37
+ "model.layers.17.mlp.gate_proj",
38
+ "model.layers.2.self_attn.o_proj",
 
 
39
  "model.layers.3.self_attn_text.k_proj",
40
+ "model.layers.0.self_attn_text.v_proj",
41
+ "model.layers.16.self_attn.q_proj",
42
+ "model.layers.4.self_attn.q_proj",
43
+ "model.layers.23.self_attn_text.o_proj",
44
+ "model.layers.12.self_attn.k_proj",
45
+ "model.layers.17.self_attn_text.v_proj",
46
+ "model.layers.25.self_attn.k_proj",
47
+ "model.layers.0.self_attn.k_proj",
48
+ "model.layers.23.self_attn.v_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
49
  "model.layers.20.self_attn.k_proj",
50
+ "model.layers.13.self_attn_text.v_proj",
51
+ "model.layers.9.self_attn.o_proj",
52
+ "model.layers.21.self_attn.v_proj",
53
+ "model.layers.11.self_attn.o_proj",
54
+ "model.layers.22.self_attn.q_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
55
  "model.layers.19.mlp.gate_proj",
56
+ "model.layers.4.mlp.gate_proj",
 
 
 
57
  "model.layers.18.self_attn.k_proj",
58
+ "model.layers.23.self_attn_text.q_proj",
59
+ "model.layers.23.self_attn.k_proj",
60
+ "model.layers.24.self_attn.k_proj",
 
 
 
 
 
 
 
61
  "model.layers.13.self_attn_text.q_proj",
62
+ "model.layers.2.self_attn.q_proj",
63
+ "model.layers.3.self_attn_text.q_proj",
64
+ "model.layers.0.self_attn_text.k_proj",
65
+ "model.layers.22.mlp.gate_proj",
66
+ "model.layers.5.mlp.down_proj",
67
+ "model.layers.11.self_attn_text.q_proj",
68
+ "model.layers.2.self_attn_text.k_proj",
69
+ "model.layers.14.self_attn_text.q_proj",
70
+ "model.layers.9.mlp.up_proj",
71
+ "model.layers.19.self_attn_text.o_proj",
72
+ "model.layers.2.self_attn_text.o_proj",
73
+ "model.layers.3.self_attn_text.v_proj",
74
+ "model.layers.27.self_attn.k_proj",
75
+ "model.layers.27.self_attn_text.v_proj",
76
+ "model.layers.7.self_attn_text.q_proj",
77
+ "model.layers.1.mlp.up_proj",
78
  "model.layers.11.self_attn.q_proj",
 
 
 
 
 
 
79
  "model.layers.8.self_attn_text.v_proj",
80
+ "model.layers.19.self_attn.k_proj",
81
+ "model.layers.24.self_attn.q_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
  "model.layers.12.self_attn_text.q_proj",
83
+ "model.layers.27.mlp.down_proj",
84
+ "model.layers.12.self_attn_text.k_proj",
85
+ "model.layers.11.self_attn.v_proj",
86
+ "model.layers.13.mlp.up_proj",
87
+ "model.layers.8.self_attn_text.q_proj",
88
+ "model.layers.22.self_attn.v_proj",
89
+ "model.layers.14.self_attn.o_proj",
90
+ "model.layers.23.self_attn.q_proj",
91
+ "model.layers.23.self_attn.o_proj",
92
  "model.layers.14.mlp.down_proj",
93
+ "model.layers.16.mlp.down_proj",
94
+ "model.layers.10.self_attn.q_proj",
95
+ "model.layers.27.mlp.up_proj",
96
+ "model.layers.17.mlp.up_proj",
97
+ "model.layers.16.self_attn_text.v_proj",
98
+ "model.layers.4.mlp.down_proj",
99
+ "model.layers.22.mlp.down_proj",
100
+ "model.layers.0.self_attn.q_proj",
101
+ "model.layers.27.mlp.gate_proj",
102
+ "model.layers.9.mlp.gate_proj",
103
+ "model.layers.22.mlp.up_proj",
104
+ "model.layers.2.self_attn.v_proj",
105
+ "model.layers.14.self_attn.q_proj",
106
+ "model.layers.7.mlp.gate_proj",
107
+ "model.layers.21.self_attn.k_proj",
108
+ "model.layers.13.self_attn.q_proj",
109
+ "model.layers.11.mlp.down_proj",
110
+ "model.layers.6.self_attn_text.k_proj",
111
+ "model.layers.16.self_attn_text.o_proj",
112
+ "model.layers.4.self_attn_text.k_proj",
113
+ "model.layers.24.self_attn_text.v_proj",
114
+ "model.layers.16.mlp.up_proj",
115
+ "model.layers.13.self_attn.k_proj",
116
+ "model.layers.5.self_attn_text.v_proj",
117
+ "model.layers.22.self_attn_text.k_proj",
118
+ "model.layers.15.self_attn_text.q_proj",
119
+ "model.layers.8.self_attn.q_proj",
120
+ "model.layers.25.self_attn_text.v_proj",
121
+ "model.layers.8.self_attn.o_proj",
122
+ "model.layers.27.self_attn_text.k_proj",
123
+ "model.layers.21.mlp.up_proj",
124
  "model.layers.9.self_attn.v_proj",
125
+ "model.layers.5.mlp.up_proj",
126
+ "model.layers.11.self_attn_text.k_proj",
127
+ "model.layers.18.mlp.up_proj",
128
  "model.layers.17.self_attn.q_proj",
129
+ "model.layers.25.mlp.down_proj",
130
+ "model.layers.16.self_attn.o_proj",
131
+ "model.layers.15.self_attn.o_proj",
132
+ "model.layers.1.mlp.down_proj",
133
+ "model.layers.24.mlp.gate_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
134
  "model.layers.10.self_attn_text.q_proj",
135
+ "model.layers.7.self_attn.k_proj",
136
+ "model.layers.7.mlp.down_proj",
137
+ "model.layers.17.self_attn_text.k_proj",
138
+ "model.layers.6.mlp.down_proj",
139
+ "model.layers.10.self_attn.k_proj",
140
+ "model.layers.17.self_attn.o_proj",
141
+ "model.layers.20.self_attn_text.q_proj",
142
+ "model.layers.26.self_attn_text.o_proj",
143
+ "model.layers.10.self_attn.v_proj",
144
+ "model.layers.20.self_attn_text.k_proj",
145
+ "model.layers.19.self_attn.o_proj",
146
+ "model.layers.8.mlp.down_proj",
147
+ "model.layers.0.mlp.down_proj",
148
  "model.layers.13.self_attn_text.o_proj",
149
+ "model.layers.18.self_attn.q_proj",
150
+ "model.layers.13.mlp.gate_proj",
151
+ "model.layers.11.self_attn_text.o_proj",
152
+ "model.layers.12.mlp.gate_proj",
153
+ "model.layers.21.mlp.gate_proj",
154
+ "model.layers.3.mlp.up_proj",
155
+ "model.layers.5.self_attn.v_proj",
156
+ "model.layers.15.self_attn.v_proj",
157
+ "model.layers.24.self_attn_text.k_proj",
158
+ "model.layers.0.self_attn_text.q_proj",
159
+ "model.layers.13.self_attn.o_proj",
160
+ "model.layers.24.mlp.down_proj",
161
+ "model.layers.26.mlp.down_proj",
162
+ "model.layers.19.mlp.up_proj",
163
+ "model.layers.17.self_attn.v_proj",
164
+ "model.layers.1.self_attn.q_proj",
165
+ "model.layers.5.self_attn_text.q_proj",
166
+ "model.layers.4.self_attn_text.q_proj",
167
+ "model.layers.18.mlp.gate_proj",
168
+ "model.layers.26.self_attn_text.v_proj",
169
+ "model.layers.8.mlp.gate_proj",
170
+ "model.layers.23.self_attn_text.v_proj",
171
+ "model.layers.26.self_attn.v_proj",
172
+ "model.layers.21.self_attn_text.q_proj",
173
+ "model.layers.26.self_attn.k_proj",
174
  "model.layers.6.mlp.gate_proj",
175
+ "model.layers.7.self_attn.o_proj",
176
+ "model.layers.26.self_attn.q_proj",
177
+ "model.layers.24.self_attn_text.o_proj",
178
+ "model.layers.17.self_attn.k_proj",
179
+ "model.layers.7.self_attn_text.o_proj",
180
+ "model.layers.24.self_attn_text.q_proj",
181
+ "model.layers.22.self_attn_text.q_proj",
182
+ "model.layers.7.self_attn.q_proj",
183
+ "model.layers.20.self_attn.v_proj",
184
  "model.layers.10.mlp.up_proj",
185
+ "model.layers.19.self_attn_text.k_proj",
186
+ "model.layers.14.self_attn_text.o_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
187
  "model.layers.22.self_attn_text.v_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
188
  "model.layers.17.mlp.down_proj",
189
+ "model.layers.16.mlp.gate_proj",
190
+ "model.layers.8.self_attn.v_proj",
191
+ "model.layers.4.self_attn_text.o_proj",
192
+ "model.layers.26.mlp.gate_proj",
193
+ "model.layers.1.mlp.gate_proj",
 
 
 
 
194
  "model.layers.18.self_attn_text.v_proj",
195
+ "model.layers.25.self_attn_text.k_proj",
196
+ "model.layers.0.mlp.gate_proj",
197
+ "model.layers.1.self_attn_text.k_proj",
198
+ "model.layers.18.self_attn_text.o_proj",
199
+ "model.layers.24.mlp.up_proj",
200
+ "model.layers.26.mlp.up_proj",
201
+ "model.layers.21.self_attn.q_proj",
 
202
  "model.layers.22.self_attn.o_proj",
203
+ "model.layers.19.self_attn.q_proj",
204
+ "model.layers.7.mlp.up_proj",
205
+ "model.layers.16.self_attn.v_proj",
206
+ "model.layers.8.mlp.up_proj",
207
+ "model.layers.10.self_attn.o_proj",
 
 
 
 
 
 
 
 
 
 
208
  "model.layers.21.self_attn_text.k_proj",
209
+ "model.layers.5.mlp.gate_proj",
210
+ "model.layers.12.mlp.up_proj",
211
+ "model.layers.25.mlp.gate_proj",
212
+ "model.layers.21.self_attn.o_proj",
213
+ "model.layers.15.self_attn_text.v_proj",
 
214
  "model.layers.15.self_attn.q_proj",
215
+ "model.layers.5.self_attn_text.o_proj",
216
+ "model.layers.12.self_attn.v_proj",
217
+ "model.layers.1.self_attn.k_proj",
218
+ "model.layers.0.self_attn_text.o_proj",
219
+ "model.layers.25.self_attn.o_proj",
220
+ "model.layers.20.self_attn_text.o_proj",
221
+ "model.layers.2.self_attn_text.q_proj",
222
+ "model.layers.6.self_attn.q_proj",
223
+ "model.layers.12.self_attn_text.v_proj",
224
+ "model.layers.18.mlp.down_proj",
225
+ "model.layers.9.self_attn.q_proj",
226
+ "model.layers.9.self_attn_text.v_proj",
227
+ "model.layers.25.mlp.up_proj",
228
+ "model.layers.16.self_attn_text.k_proj",
229
+ "model.layers.12.self_attn_text.o_proj",
230
+ "model.layers.18.self_attn_text.q_proj",
231
+ "model.layers.13.mlp.down_proj",
232
+ "model.layers.19.mlp.down_proj",
233
+ "model.layers.17.self_attn_text.o_proj",
234
+ "model.layers.27.self_attn.v_proj",
235
+ "model.layers.12.self_attn.o_proj",
236
+ "model.layers.1.self_attn_text.o_proj",
237
+ "model.layers.13.self_attn.v_proj",
238
+ "model.layers.23.mlp.up_proj",
239
+ "model.layers.15.self_attn_text.k_proj",
240
+ "model.layers.5.self_attn.o_proj",
241
  "model.layers.0.self_attn.o_proj",
242
+ "model.layers.13.self_attn_text.k_proj",
243
+ "model.layers.21.self_attn_text.o_proj",
244
+ "model.layers.3.self_attn.v_proj",
245
+ "model.layers.6.self_attn.o_proj",
246
+ "model.layers.4.self_attn.k_proj",
247
+ "model.layers.1.self_attn.v_proj",
248
  "model.layers.4.self_attn_text.v_proj",
249
+ "model.layers.5.self_attn_text.k_proj",
250
+ "model.layers.14.self_attn_text.v_proj",
251
+ "model.layers.19.self_attn.v_proj",
252
+ "model.layers.12.mlp.down_proj",
253
+ "model.layers.14.mlp.up_proj",
254
+ "model.layers.10.self_attn_text.v_proj",
255
+ "model.layers.2.mlp.down_proj",
256
+ "model.layers.3.mlp.down_proj",
257
  "model.layers.14.self_attn_text.k_proj",
258
+ "model.layers.23.self_attn_text.k_proj",
259
+ "model.layers.23.mlp.down_proj",
260
+ "model.layers.25.self_attn_text.q_proj",
261
+ "model.layers.7.self_attn.v_proj",
262
+ "model.layers.10.self_attn_text.k_proj",
263
+ "model.layers.23.mlp.gate_proj",
264
+ "model.layers.8.self_attn_text.k_proj",
 
 
 
 
 
 
 
 
 
 
 
 
 
265
  "model.layers.19.self_attn_text.q_proj",
266
+ "model.layers.15.self_attn_text.o_proj",
267
+ "model.layers.3.self_attn_text.o_proj",
268
+ "model.layers.12.self_attn.q_proj",
269
+ "model.layers.14.self_attn.k_proj",
270
+ "model.layers.18.self_attn.o_proj",
271
+ "model.layers.0.mlp.up_proj",
272
+ "model.layers.4.self_attn.v_proj",
273
+ "model.layers.10.mlp.down_proj",
274
+ "model.layers.25.self_attn.v_proj",
275
+ "model.layers.21.self_attn_text.v_proj",
276
+ "model.layers.15.self_attn.k_proj",
277
+ "model.layers.21.mlp.down_proj",
278
+ "model.layers.27.self_attn_text.q_proj",
279
+ "model.layers.15.mlp.down_proj",
280
+ "model.layers.24.self_attn.v_proj",
281
+ "model.layers.15.mlp.up_proj",
282
+ "model.layers.9.self_attn.k_proj",
283
+ "model.layers.2.self_attn_text.v_proj",
284
+ "model.layers.3.self_attn.q_proj",
285
+ "model.layers.27.self_attn_text.o_proj",
286
+ "model.layers.8.self_attn_text.o_proj",
287
+ "model.layers.11.self_attn_text.v_proj",
288
+ "model.layers.18.self_attn.v_proj",
289
+ "model.layers.6.self_attn_text.o_proj",
290
+ "model.layers.1.self_attn_text.q_proj",
291
+ "model.layers.14.mlp.gate_proj",
292
+ "model.layers.6.self_attn_text.v_proj",
293
+ "model.layers.4.mlp.up_proj",
294
+ "model.layers.9.self_attn_text.o_proj",
295
  "model.layers.20.self_attn_text.v_proj",
296
+ "model.layers.9.self_attn_text.q_proj",
297
+ "model.layers.14.self_attn.v_proj",
298
+ "model.layers.27.self_attn.o_proj",
299
+ "model.layers.10.mlp.gate_proj",
300
+ "model.layers.26.self_attn.o_proj",
301
+ "model.layers.25.self_attn_text.o_proj",
302
+ "model.layers.9.self_attn_text.k_proj",
303
+ "model.layers.5.self_attn.q_proj",
304
+ "model.layers.3.mlp.gate_proj",
305
+ "model.layers.15.mlp.gate_proj",
306
  "model.layers.16.self_attn.k_proj",
307
+ "model.layers.2.mlp.gate_proj",
308
+ "model.layers.2.mlp.up_proj",
309
+ "model.layers.26.self_attn_text.q_proj",
310
+ "model.layers.17.self_attn_text.q_proj",
311
  "model.layers.24.self_attn.o_proj",
312
+ "model.layers.0.self_attn.v_proj",
313
+ "model.layers.7.self_attn_text.v_proj",
314
+ "model.layers.20.mlp.down_proj",
315
+ "model.layers.20.mlp.gate_proj",
316
+ "model.layers.9.mlp.down_proj",
317
+ "model.layers.16.self_attn_text.q_proj",
318
+ "model.layers.11.self_attn.k_proj",
319
+ "model.layers.3.self_attn.o_proj",
320
+ "model.layers.19.self_attn_text.v_proj",
321
+ "model.layers.1.self_attn_text.v_proj",
322
+ "model.layers.11.mlp.gate_proj",
323
+ "model.layers.11.mlp.up_proj",
324
+ "model.layers.22.self_attn_text.o_proj",
325
+ "model.layers.26.self_attn_text.k_proj",
326
+ "model.layers.6.mlp.up_proj",
327
+ "model.layers.4.self_attn.o_proj",
328
+ "model.layers.27.self_attn.q_proj",
329
+ "model.layers.20.mlp.up_proj",
330
+ "model.layers.6.self_attn_text.q_proj"
331
  ],
332
  "task_type": "CAUSAL_LM",
333
  "use_dora": false,
adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:845f34c1f221b697726779b3fd71e1029e7d68df2e0d70cd0bb291bb74d0558a
3
- size 133350944
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a2e986c7024b9ca65e4e32ac4d78394410d178075d7900e4970cc747eed3bc2
3
+ size 91374880
all_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
- "epoch": 24.608,
3
- "total_flos": 1.324081921088553e+17,
4
- "train_loss": 0.672794044127147,
5
- "train_runtime": 33908.1665,
6
- "train_samples_per_second": 0.369,
7
- "train_steps_per_second": 0.046
8
  }
 
1
  {
2
+ "epoch": 14.544,
3
+ "total_flos": 1.565274744469586e+17,
4
+ "train_loss": 1.4569768874875961,
5
+ "train_runtime": 22995.3507,
6
+ "train_samples_per_second": 0.652,
7
+ "train_steps_per_second": 0.02
8
  }
checkpoint-465/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: saim1212/penguin2
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.12.0
checkpoint-465/adapter_config.json ADDED
@@ -0,0 +1,335 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "saim1212/penguin2",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 16,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "model.layers.6.self_attn.v_proj",
24
+ "model.layers.3.self_attn.k_proj",
25
+ "model.layers.5.self_attn.k_proj",
26
+ "model.layers.20.self_attn.o_proj",
27
+ "model.layers.2.self_attn.k_proj",
28
+ "model.layers.7.self_attn_text.k_proj",
29
+ "model.layers.6.self_attn.k_proj",
30
+ "model.layers.20.self_attn.q_proj",
31
+ "model.layers.25.self_attn.q_proj",
32
+ "model.layers.1.self_attn.o_proj",
33
+ "model.layers.22.self_attn.k_proj",
34
+ "model.layers.8.self_attn.k_proj",
35
+ "model.layers.18.self_attn_text.k_proj",
36
+ "model.layers.10.self_attn_text.o_proj",
37
+ "model.layers.17.mlp.gate_proj",
38
+ "model.layers.2.self_attn.o_proj",
39
+ "model.layers.3.self_attn_text.k_proj",
40
+ "model.layers.0.self_attn_text.v_proj",
41
+ "model.layers.16.self_attn.q_proj",
42
+ "model.layers.4.self_attn.q_proj",
43
+ "model.layers.23.self_attn_text.o_proj",
44
+ "model.layers.12.self_attn.k_proj",
45
+ "model.layers.17.self_attn_text.v_proj",
46
+ "model.layers.25.self_attn.k_proj",
47
+ "model.layers.0.self_attn.k_proj",
48
+ "model.layers.23.self_attn.v_proj",
49
+ "model.layers.20.self_attn.k_proj",
50
+ "model.layers.13.self_attn_text.v_proj",
51
+ "model.layers.9.self_attn.o_proj",
52
+ "model.layers.21.self_attn.v_proj",
53
+ "model.layers.11.self_attn.o_proj",
54
+ "model.layers.22.self_attn.q_proj",
55
+ "model.layers.19.mlp.gate_proj",
56
+ "model.layers.4.mlp.gate_proj",
57
+ "model.layers.18.self_attn.k_proj",
58
+ "model.layers.23.self_attn_text.q_proj",
59
+ "model.layers.23.self_attn.k_proj",
60
+ "model.layers.24.self_attn.k_proj",
61
+ "model.layers.13.self_attn_text.q_proj",
62
+ "model.layers.2.self_attn.q_proj",
63
+ "model.layers.3.self_attn_text.q_proj",
64
+ "model.layers.0.self_attn_text.k_proj",
65
+ "model.layers.22.mlp.gate_proj",
66
+ "model.layers.5.mlp.down_proj",
67
+ "model.layers.11.self_attn_text.q_proj",
68
+ "model.layers.2.self_attn_text.k_proj",
69
+ "model.layers.14.self_attn_text.q_proj",
70
+ "model.layers.9.mlp.up_proj",
71
+ "model.layers.19.self_attn_text.o_proj",
72
+ "model.layers.2.self_attn_text.o_proj",
73
+ "model.layers.3.self_attn_text.v_proj",
74
+ "model.layers.27.self_attn.k_proj",
75
+ "model.layers.27.self_attn_text.v_proj",
76
+ "model.layers.7.self_attn_text.q_proj",
77
+ "model.layers.1.mlp.up_proj",
78
+ "model.layers.11.self_attn.q_proj",
79
+ "model.layers.8.self_attn_text.v_proj",
80
+ "model.layers.19.self_attn.k_proj",
81
+ "model.layers.24.self_attn.q_proj",
82
+ "model.layers.12.self_attn_text.q_proj",
83
+ "model.layers.27.mlp.down_proj",
84
+ "model.layers.12.self_attn_text.k_proj",
85
+ "model.layers.11.self_attn.v_proj",
86
+ "model.layers.13.mlp.up_proj",
87
+ "model.layers.8.self_attn_text.q_proj",
88
+ "model.layers.22.self_attn.v_proj",
89
+ "model.layers.14.self_attn.o_proj",
90
+ "model.layers.23.self_attn.q_proj",
91
+ "model.layers.23.self_attn.o_proj",
92
+ "model.layers.14.mlp.down_proj",
93
+ "model.layers.16.mlp.down_proj",
94
+ "model.layers.10.self_attn.q_proj",
95
+ "model.layers.27.mlp.up_proj",
96
+ "model.layers.17.mlp.up_proj",
97
+ "model.layers.16.self_attn_text.v_proj",
98
+ "model.layers.4.mlp.down_proj",
99
+ "model.layers.22.mlp.down_proj",
100
+ "model.layers.0.self_attn.q_proj",
101
+ "model.layers.27.mlp.gate_proj",
102
+ "model.layers.9.mlp.gate_proj",
103
+ "model.layers.22.mlp.up_proj",
104
+ "model.layers.2.self_attn.v_proj",
105
+ "model.layers.14.self_attn.q_proj",
106
+ "model.layers.7.mlp.gate_proj",
107
+ "model.layers.21.self_attn.k_proj",
108
+ "model.layers.13.self_attn.q_proj",
109
+ "model.layers.11.mlp.down_proj",
110
+ "model.layers.6.self_attn_text.k_proj",
111
+ "model.layers.16.self_attn_text.o_proj",
112
+ "model.layers.4.self_attn_text.k_proj",
113
+ "model.layers.24.self_attn_text.v_proj",
114
+ "model.layers.16.mlp.up_proj",
115
+ "model.layers.13.self_attn.k_proj",
116
+ "model.layers.5.self_attn_text.v_proj",
117
+ "model.layers.22.self_attn_text.k_proj",
118
+ "model.layers.15.self_attn_text.q_proj",
119
+ "model.layers.8.self_attn.q_proj",
120
+ "model.layers.25.self_attn_text.v_proj",
121
+ "model.layers.8.self_attn.o_proj",
122
+ "model.layers.27.self_attn_text.k_proj",
123
+ "model.layers.21.mlp.up_proj",
124
+ "model.layers.9.self_attn.v_proj",
125
+ "model.layers.5.mlp.up_proj",
126
+ "model.layers.11.self_attn_text.k_proj",
127
+ "model.layers.18.mlp.up_proj",
128
+ "model.layers.17.self_attn.q_proj",
129
+ "model.layers.25.mlp.down_proj",
130
+ "model.layers.16.self_attn.o_proj",
131
+ "model.layers.15.self_attn.o_proj",
132
+ "model.layers.1.mlp.down_proj",
133
+ "model.layers.24.mlp.gate_proj",
134
+ "model.layers.10.self_attn_text.q_proj",
135
+ "model.layers.7.self_attn.k_proj",
136
+ "model.layers.7.mlp.down_proj",
137
+ "model.layers.17.self_attn_text.k_proj",
138
+ "model.layers.6.mlp.down_proj",
139
+ "model.layers.10.self_attn.k_proj",
140
+ "model.layers.17.self_attn.o_proj",
141
+ "model.layers.20.self_attn_text.q_proj",
142
+ "model.layers.26.self_attn_text.o_proj",
143
+ "model.layers.10.self_attn.v_proj",
144
+ "model.layers.20.self_attn_text.k_proj",
145
+ "model.layers.19.self_attn.o_proj",
146
+ "model.layers.8.mlp.down_proj",
147
+ "model.layers.0.mlp.down_proj",
148
+ "model.layers.13.self_attn_text.o_proj",
149
+ "model.layers.18.self_attn.q_proj",
150
+ "model.layers.13.mlp.gate_proj",
151
+ "model.layers.11.self_attn_text.o_proj",
152
+ "model.layers.12.mlp.gate_proj",
153
+ "model.layers.21.mlp.gate_proj",
154
+ "model.layers.3.mlp.up_proj",
155
+ "model.layers.5.self_attn.v_proj",
156
+ "model.layers.15.self_attn.v_proj",
157
+ "model.layers.24.self_attn_text.k_proj",
158
+ "model.layers.0.self_attn_text.q_proj",
159
+ "model.layers.13.self_attn.o_proj",
160
+ "model.layers.24.mlp.down_proj",
161
+ "model.layers.26.mlp.down_proj",
162
+ "model.layers.19.mlp.up_proj",
163
+ "model.layers.17.self_attn.v_proj",
164
+ "model.layers.1.self_attn.q_proj",
165
+ "model.layers.5.self_attn_text.q_proj",
166
+ "model.layers.4.self_attn_text.q_proj",
167
+ "model.layers.18.mlp.gate_proj",
168
+ "model.layers.26.self_attn_text.v_proj",
169
+ "model.layers.8.mlp.gate_proj",
170
+ "model.layers.23.self_attn_text.v_proj",
171
+ "model.layers.26.self_attn.v_proj",
172
+ "model.layers.21.self_attn_text.q_proj",
173
+ "model.layers.26.self_attn.k_proj",
174
+ "model.layers.6.mlp.gate_proj",
175
+ "model.layers.7.self_attn.o_proj",
176
+ "model.layers.26.self_attn.q_proj",
177
+ "model.layers.24.self_attn_text.o_proj",
178
+ "model.layers.17.self_attn.k_proj",
179
+ "model.layers.7.self_attn_text.o_proj",
180
+ "model.layers.24.self_attn_text.q_proj",
181
+ "model.layers.22.self_attn_text.q_proj",
182
+ "model.layers.7.self_attn.q_proj",
183
+ "model.layers.20.self_attn.v_proj",
184
+ "model.layers.10.mlp.up_proj",
185
+ "model.layers.19.self_attn_text.k_proj",
186
+ "model.layers.14.self_attn_text.o_proj",
187
+ "model.layers.22.self_attn_text.v_proj",
188
+ "model.layers.17.mlp.down_proj",
189
+ "model.layers.16.mlp.gate_proj",
190
+ "model.layers.8.self_attn.v_proj",
191
+ "model.layers.4.self_attn_text.o_proj",
192
+ "model.layers.26.mlp.gate_proj",
193
+ "model.layers.1.mlp.gate_proj",
194
+ "model.layers.18.self_attn_text.v_proj",
195
+ "model.layers.25.self_attn_text.k_proj",
196
+ "model.layers.0.mlp.gate_proj",
197
+ "model.layers.1.self_attn_text.k_proj",
198
+ "model.layers.18.self_attn_text.o_proj",
199
+ "model.layers.24.mlp.up_proj",
200
+ "model.layers.26.mlp.up_proj",
201
+ "model.layers.21.self_attn.q_proj",
202
+ "model.layers.22.self_attn.o_proj",
203
+ "model.layers.19.self_attn.q_proj",
204
+ "model.layers.7.mlp.up_proj",
205
+ "model.layers.16.self_attn.v_proj",
206
+ "model.layers.8.mlp.up_proj",
207
+ "model.layers.10.self_attn.o_proj",
208
+ "model.layers.21.self_attn_text.k_proj",
209
+ "model.layers.5.mlp.gate_proj",
210
+ "model.layers.12.mlp.up_proj",
211
+ "model.layers.25.mlp.gate_proj",
212
+ "model.layers.21.self_attn.o_proj",
213
+ "model.layers.15.self_attn_text.v_proj",
214
+ "model.layers.15.self_attn.q_proj",
215
+ "model.layers.5.self_attn_text.o_proj",
216
+ "model.layers.12.self_attn.v_proj",
217
+ "model.layers.1.self_attn.k_proj",
218
+ "model.layers.0.self_attn_text.o_proj",
219
+ "model.layers.25.self_attn.o_proj",
220
+ "model.layers.20.self_attn_text.o_proj",
221
+ "model.layers.2.self_attn_text.q_proj",
222
+ "model.layers.6.self_attn.q_proj",
223
+ "model.layers.12.self_attn_text.v_proj",
224
+ "model.layers.18.mlp.down_proj",
225
+ "model.layers.9.self_attn.q_proj",
226
+ "model.layers.9.self_attn_text.v_proj",
227
+ "model.layers.25.mlp.up_proj",
228
+ "model.layers.16.self_attn_text.k_proj",
229
+ "model.layers.12.self_attn_text.o_proj",
230
+ "model.layers.18.self_attn_text.q_proj",
231
+ "model.layers.13.mlp.down_proj",
232
+ "model.layers.19.mlp.down_proj",
233
+ "model.layers.17.self_attn_text.o_proj",
234
+ "model.layers.27.self_attn.v_proj",
235
+ "model.layers.12.self_attn.o_proj",
236
+ "model.layers.1.self_attn_text.o_proj",
237
+ "model.layers.13.self_attn.v_proj",
238
+ "model.layers.23.mlp.up_proj",
239
+ "model.layers.15.self_attn_text.k_proj",
240
+ "model.layers.5.self_attn.o_proj",
241
+ "model.layers.0.self_attn.o_proj",
242
+ "model.layers.13.self_attn_text.k_proj",
243
+ "model.layers.21.self_attn_text.o_proj",
244
+ "model.layers.3.self_attn.v_proj",
245
+ "model.layers.6.self_attn.o_proj",
246
+ "model.layers.4.self_attn.k_proj",
247
+ "model.layers.1.self_attn.v_proj",
248
+ "model.layers.4.self_attn_text.v_proj",
249
+ "model.layers.5.self_attn_text.k_proj",
250
+ "model.layers.14.self_attn_text.v_proj",
251
+ "model.layers.19.self_attn.v_proj",
252
+ "model.layers.12.mlp.down_proj",
253
+ "model.layers.14.mlp.up_proj",
254
+ "model.layers.10.self_attn_text.v_proj",
255
+ "model.layers.2.mlp.down_proj",
256
+ "model.layers.3.mlp.down_proj",
257
+ "model.layers.14.self_attn_text.k_proj",
258
+ "model.layers.23.self_attn_text.k_proj",
259
+ "model.layers.23.mlp.down_proj",
260
+ "model.layers.25.self_attn_text.q_proj",
261
+ "model.layers.7.self_attn.v_proj",
262
+ "model.layers.10.self_attn_text.k_proj",
263
+ "model.layers.23.mlp.gate_proj",
264
+ "model.layers.8.self_attn_text.k_proj",
265
+ "model.layers.19.self_attn_text.q_proj",
266
+ "model.layers.15.self_attn_text.o_proj",
267
+ "model.layers.3.self_attn_text.o_proj",
268
+ "model.layers.12.self_attn.q_proj",
269
+ "model.layers.14.self_attn.k_proj",
270
+ "model.layers.18.self_attn.o_proj",
271
+ "model.layers.0.mlp.up_proj",
272
+ "model.layers.4.self_attn.v_proj",
273
+ "model.layers.10.mlp.down_proj",
274
+ "model.layers.25.self_attn.v_proj",
275
+ "model.layers.21.self_attn_text.v_proj",
276
+ "model.layers.15.self_attn.k_proj",
277
+ "model.layers.21.mlp.down_proj",
278
+ "model.layers.27.self_attn_text.q_proj",
279
+ "model.layers.15.mlp.down_proj",
280
+ "model.layers.24.self_attn.v_proj",
281
+ "model.layers.15.mlp.up_proj",
282
+ "model.layers.9.self_attn.k_proj",
283
+ "model.layers.2.self_attn_text.v_proj",
284
+ "model.layers.3.self_attn.q_proj",
285
+ "model.layers.27.self_attn_text.o_proj",
286
+ "model.layers.8.self_attn_text.o_proj",
287
+ "model.layers.11.self_attn_text.v_proj",
288
+ "model.layers.18.self_attn.v_proj",
289
+ "model.layers.6.self_attn_text.o_proj",
290
+ "model.layers.1.self_attn_text.q_proj",
291
+ "model.layers.14.mlp.gate_proj",
292
+ "model.layers.6.self_attn_text.v_proj",
293
+ "model.layers.4.mlp.up_proj",
294
+ "model.layers.9.self_attn_text.o_proj",
295
+ "model.layers.20.self_attn_text.v_proj",
296
+ "model.layers.9.self_attn_text.q_proj",
297
+ "model.layers.14.self_attn.v_proj",
298
+ "model.layers.27.self_attn.o_proj",
299
+ "model.layers.10.mlp.gate_proj",
300
+ "model.layers.26.self_attn.o_proj",
301
+ "model.layers.25.self_attn_text.o_proj",
302
+ "model.layers.9.self_attn_text.k_proj",
303
+ "model.layers.5.self_attn.q_proj",
304
+ "model.layers.3.mlp.gate_proj",
305
+ "model.layers.15.mlp.gate_proj",
306
+ "model.layers.16.self_attn.k_proj",
307
+ "model.layers.2.mlp.gate_proj",
308
+ "model.layers.2.mlp.up_proj",
309
+ "model.layers.26.self_attn_text.q_proj",
310
+ "model.layers.17.self_attn_text.q_proj",
311
+ "model.layers.24.self_attn.o_proj",
312
+ "model.layers.0.self_attn.v_proj",
313
+ "model.layers.7.self_attn_text.v_proj",
314
+ "model.layers.20.mlp.down_proj",
315
+ "model.layers.20.mlp.gate_proj",
316
+ "model.layers.9.mlp.down_proj",
317
+ "model.layers.16.self_attn_text.q_proj",
318
+ "model.layers.11.self_attn.k_proj",
319
+ "model.layers.3.self_attn.o_proj",
320
+ "model.layers.19.self_attn_text.v_proj",
321
+ "model.layers.1.self_attn_text.v_proj",
322
+ "model.layers.11.mlp.gate_proj",
323
+ "model.layers.11.mlp.up_proj",
324
+ "model.layers.22.self_attn_text.o_proj",
325
+ "model.layers.26.self_attn_text.k_proj",
326
+ "model.layers.6.mlp.up_proj",
327
+ "model.layers.4.self_attn.o_proj",
328
+ "model.layers.27.self_attn.q_proj",
329
+ "model.layers.20.mlp.up_proj",
330
+ "model.layers.6.self_attn_text.q_proj"
331
+ ],
332
+ "task_type": "CAUSAL_LM",
333
+ "use_dora": false,
334
+ "use_rslora": false
335
+ }
checkpoint-465/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a2e986c7024b9ca65e4e32ac4d78394410d178075d7900e4970cc747eed3bc2
3
+ size 91374880
checkpoint-465/added_tokens.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "<|box_end|>": 151649,
3
+ "<|box_start|>": 151648,
4
+ "<|endoftext|>": 151643,
5
+ "<|im_end|>": 151645,
6
+ "<|im_start|>": 151644,
7
+ "<|image_pad|>": 151655,
8
+ "<|object_ref_end|>": 151647,
9
+ "<|object_ref_start|>": 151646,
10
+ "<|quad_end|>": 151651,
11
+ "<|quad_start|>": 151650,
12
+ "<|video_pad|>": 151656,
13
+ "<|vision_end|>": 151653,
14
+ "<|vision_pad|>": 151654,
15
+ "<|vision_start|>": 151652
16
+ }
checkpoint-465/chat_template.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
3
+ }
checkpoint-465/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-465/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:755a9ee43ca8b7fb7c2076175b0b21246789d68e9304c029a8e85e64ea08958b
3
+ size 183102410
checkpoint-465/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": true,
3
+ "do_normalize": true,
4
+ "do_rescale": true,
5
+ "do_resize": true,
6
+ "image_mean": [
7
+ 0.48145466,
8
+ 0.4578275,
9
+ 0.40821073
10
+ ],
11
+ "image_processor_type": "Qwen2VLImageProcessor",
12
+ "image_std": [
13
+ 0.26862954,
14
+ 0.26130258,
15
+ 0.27577711
16
+ ],
17
+ "max_pixels": 12845056,
18
+ "merge_size": 2,
19
+ "min_pixels": 3136,
20
+ "patch_size": 14,
21
+ "processor_class": "Qwen2VLProcessor",
22
+ "resample": 3,
23
+ "rescale_factor": 0.00392156862745098,
24
+ "size": {
25
+ "longest_edge": 12845056,
26
+ "shortest_edge": 3136
27
+ },
28
+ "temporal_patch_size": 2
29
+ }
checkpoint-465/rng_state_0.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0b72d3ff0d9cef769a20852fa3473da68a2ad59950ff6438edf98c95328ba5c1
3
+ size 14512
checkpoint-465/rng_state_1.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bff6047902e34b76f0af39d44c10111f1acce1cfd48509bfb6b92e02a5c71d0f
3
+ size 14512
checkpoint-465/scaler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:818fc610f189557fd0fe4d05b146765e846d07979610f421578552c74e693478
3
+ size 988
checkpoint-465/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ec8cbb7526bfeebe005e6092a1c9c3f561b1a9f8e4976ac114e936a719f46ca5
3
+ size 1064
checkpoint-465/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
checkpoint-465/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:091aa7594dc2fcfbfa06b9e3c22a5f0562ac14f30375c13af7309407a0e67b8a
3
+ size 11420371
checkpoint-465/tokenizer_config.json ADDED
@@ -0,0 +1,148 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "151643": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "151644": {
13
+ "content": "<|im_start|>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "151645": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ },
28
+ "151646": {
29
+ "content": "<|object_ref_start|>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
35
+ },
36
+ "151647": {
37
+ "content": "<|object_ref_end|>",
38
+ "lstrip": false,
39
+ "normalized": false,
40
+ "rstrip": false,
41
+ "single_word": false,
42
+ "special": true
43
+ },
44
+ "151648": {
45
+ "content": "<|box_start|>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
52
+ "151649": {
53
+ "content": "<|box_end|>",
54
+ "lstrip": false,
55
+ "normalized": false,
56
+ "rstrip": false,
57
+ "single_word": false,
58
+ "special": true
59
+ },
60
+ "151650": {
61
+ "content": "<|quad_start|>",
62
+ "lstrip": false,
63
+ "normalized": false,
64
+ "rstrip": false,
65
+ "single_word": false,
66
+ "special": true
67
+ },
68
+ "151651": {
69
+ "content": "<|quad_end|>",
70
+ "lstrip": false,
71
+ "normalized": false,
72
+ "rstrip": false,
73
+ "single_word": false,
74
+ "special": true
75
+ },
76
+ "151652": {
77
+ "content": "<|vision_start|>",
78
+ "lstrip": false,
79
+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
82
+ "special": true
83
+ },
84
+ "151653": {
85
+ "content": "<|vision_end|>",
86
+ "lstrip": false,
87
+ "normalized": false,
88
+ "rstrip": false,
89
+ "single_word": false,
90
+ "special": true
91
+ },
92
+ "151654": {
93
+ "content": "<|vision_pad|>",
94
+ "lstrip": false,
95
+ "normalized": false,
96
+ "rstrip": false,
97
+ "single_word": false,
98
+ "special": true
99
+ },
100
+ "151655": {
101
+ "content": "<|image_pad|>",
102
+ "lstrip": false,
103
+ "normalized": false,
104
+ "rstrip": false,
105
+ "single_word": false,
106
+ "special": true
107
+ },
108
+ "151656": {
109
+ "content": "<|video_pad|>",
110
+ "lstrip": false,
111
+ "normalized": false,
112
+ "rstrip": false,
113
+ "single_word": false,
114
+ "special": true
115
+ }
116
+ },
117
+ "additional_special_tokens": [
118
+ "<|im_start|>",
119
+ "<|im_end|>",
120
+ "<|object_ref_start|>",
121
+ "<|object_ref_end|>",
122
+ "<|box_start|>",
123
+ "<|box_end|>",
124
+ "<|quad_start|>",
125
+ "<|quad_end|>",
126
+ "<|vision_start|>",
127
+ "<|vision_end|>",
128
+ "<|vision_pad|>",
129
+ "<|image_pad|>",
130
+ "<|video_pad|>"
131
+ ],
132
+ "bos_token": null,
133
+ "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
134
+ "clean_up_tokenization_spaces": false,
135
+ "eos_token": "<|im_end|>",
136
+ "errors": "replace",
137
+ "extra_special_tokens": {},
138
+ "max_length": null,
139
+ "model_max_length": 32768,
140
+ "pad_to_multiple_of": null,
141
+ "pad_token": "<|endoftext|>",
142
+ "pad_token_type_id": 0,
143
+ "padding_side": "right",
144
+ "processor_class": "Qwen2VLProcessor",
145
+ "split_special_tokens": false,
146
+ "tokenizer_class": "Qwen2Tokenizer",
147
+ "unk_token": null
148
+ }
checkpoint-465/trainer_state.json ADDED
@@ -0,0 +1,355 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 14.544,
5
+ "eval_steps": 500,
6
+ "global_step": 465,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.32,
13
+ "grad_norm": 72.67546081542969,
14
+ "learning_rate": 3.8297872340425535e-06,
15
+ "loss": 10.0348,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.64,
20
+ "grad_norm": 41.243839263916016,
21
+ "learning_rate": 8.085106382978723e-06,
22
+ "loss": 4.7312,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.96,
27
+ "grad_norm": 34.776241302490234,
28
+ "learning_rate": 1.2340425531914895e-05,
29
+ "loss": 3.4362,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 1.256,
34
+ "grad_norm": 12.210166931152344,
35
+ "learning_rate": 1.6595744680851064e-05,
36
+ "loss": 2.5739,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 1.576,
41
+ "grad_norm": 11.936144828796387,
42
+ "learning_rate": 1.9998870284726968e-05,
43
+ "loss": 2.4828,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 1.896,
48
+ "grad_norm": 5.305131912231445,
49
+ "learning_rate": 1.9959357045100764e-05,
50
+ "loss": 2.1904,
51
+ "step": 60
52
+ },
53
+ {
54
+ "epoch": 2.192,
55
+ "grad_norm": 6.481784820556641,
56
+ "learning_rate": 1.9863613034027224e-05,
57
+ "loss": 1.893,
58
+ "step": 70
59
+ },
60
+ {
61
+ "epoch": 2.512,
62
+ "grad_norm": 2.9933059215545654,
63
+ "learning_rate": 1.971217882451521e-05,
64
+ "loss": 1.9328,
65
+ "step": 80
66
+ },
67
+ {
68
+ "epoch": 2.832,
69
+ "grad_norm": 5.0720906257629395,
70
+ "learning_rate": 1.9505909417784758e-05,
71
+ "loss": 1.8361,
72
+ "step": 90
73
+ },
74
+ {
75
+ "epoch": 3.128,
76
+ "grad_norm": 4.453537940979004,
77
+ "learning_rate": 1.9245969415909464e-05,
78
+ "loss": 1.6677,
79
+ "step": 100
80
+ },
81
+ {
82
+ "epoch": 3.448,
83
+ "grad_norm": 3.9254183769226074,
84
+ "learning_rate": 1.8933826446444933e-05,
85
+ "loss": 1.7492,
86
+ "step": 110
87
+ },
88
+ {
89
+ "epoch": 3.768,
90
+ "grad_norm": 2.421752691268921,
91
+ "learning_rate": 1.8571242876167995e-05,
92
+ "loss": 1.6435,
93
+ "step": 120
94
+ },
95
+ {
96
+ "epoch": 4.064,
97
+ "grad_norm": 3.5012094974517822,
98
+ "learning_rate": 1.8160265860711134e-05,
99
+ "loss": 1.478,
100
+ "step": 130
101
+ },
102
+ {
103
+ "epoch": 4.384,
104
+ "grad_norm": 4.192974090576172,
105
+ "learning_rate": 1.770321578627213e-05,
106
+ "loss": 1.4807,
107
+ "step": 140
108
+ },
109
+ {
110
+ "epoch": 4.704,
111
+ "grad_norm": 2.528031826019287,
112
+ "learning_rate": 1.7202673168657318e-05,
113
+ "loss": 1.375,
114
+ "step": 150
115
+ },
116
+ {
117
+ "epoch": 5.0,
118
+ "grad_norm": 1.0680221319198608,
119
+ "learning_rate": 1.6661464083626734e-05,
120
+ "loss": 1.2751,
121
+ "step": 160
122
+ },
123
+ {
124
+ "epoch": 5.32,
125
+ "grad_norm": 2.499868392944336,
126
+ "learning_rate": 1.6082644210801846e-05,
127
+ "loss": 1.2887,
128
+ "step": 170
129
+ },
130
+ {
131
+ "epoch": 5.64,
132
+ "grad_norm": 2.785773754119873,
133
+ "learning_rate": 1.5469481581224274e-05,
134
+ "loss": 1.2852,
135
+ "step": 180
136
+ },
137
+ {
138
+ "epoch": 5.96,
139
+ "grad_norm": 2.820884943008423,
140
+ "learning_rate": 1.4825438125973263e-05,
141
+ "loss": 1.2329,
142
+ "step": 190
143
+ },
144
+ {
145
+ "epoch": 6.256,
146
+ "grad_norm": 2.5425021648406982,
147
+ "learning_rate": 1.4154150130018867e-05,
148
+ "loss": 1.1001,
149
+ "step": 200
150
+ },
151
+ {
152
+ "epoch": 6.576,
153
+ "grad_norm": 2.7974514961242676,
154
+ "learning_rate": 1.3459407701668762e-05,
155
+ "loss": 1.1543,
156
+ "step": 210
157
+ },
158
+ {
159
+ "epoch": 6.896,
160
+ "grad_norm": 2.438002586364746,
161
+ "learning_rate": 1.2745133373524855e-05,
162
+ "loss": 1.132,
163
+ "step": 220
164
+ },
165
+ {
166
+ "epoch": 7.192,
167
+ "grad_norm": 2.9781107902526855,
168
+ "learning_rate": 1.2015359955769021e-05,
169
+ "loss": 1.0284,
170
+ "step": 230
171
+ },
172
+ {
173
+ "epoch": 7.5120000000000005,
174
+ "grad_norm": 3.271495819091797,
175
+ "learning_rate": 1.127420776681905e-05,
176
+ "loss": 1.0392,
177
+ "step": 240
178
+ },
179
+ {
180
+ "epoch": 7.832,
181
+ "grad_norm": 3.1173477172851562,
182
+ "learning_rate": 1.0525861369910877e-05,
183
+ "loss": 1.0436,
184
+ "step": 250
185
+ },
186
+ {
187
+ "epoch": 8.128,
188
+ "grad_norm": 2.84490704536438,
189
+ "learning_rate": 9.77454594695308e-06,
190
+ "loss": 0.8973,
191
+ "step": 260
192
+ },
193
+ {
194
+ "epoch": 8.448,
195
+ "grad_norm": 3.3770253658294678,
196
+ "learning_rate": 9.024503443047318e-06,
197
+ "loss": 0.9455,
198
+ "step": 270
199
+ },
200
+ {
201
+ "epoch": 8.768,
202
+ "grad_norm": 3.168492317199707,
203
+ "learning_rate": 8.279968616363417e-06,
204
+ "loss": 0.9297,
205
+ "step": 280
206
+ },
207
+ {
208
+ "epoch": 9.064,
209
+ "grad_norm": 3.5850722789764404,
210
+ "learning_rate": 7.545145128592009e-06,
211
+ "loss": 0.8414,
212
+ "step": 290
213
+ },
214
+ {
215
+ "epoch": 9.384,
216
+ "grad_norm": 2.5484402179718018,
217
+ "learning_rate": 6.824181810968675e-06,
218
+ "loss": 0.8513,
219
+ "step": 300
220
+ },
221
+ {
222
+ "epoch": 9.704,
223
+ "grad_norm": 3.354924201965332,
224
+ "learning_rate": 6.121149239872151e-06,
225
+ "loss": 0.8351,
226
+ "step": 310
227
+ },
228
+ {
229
+ "epoch": 10.0,
230
+ "grad_norm": 1.4634054899215698,
231
+ "learning_rate": 5.440016754251364e-06,
232
+ "loss": 0.7886,
233
+ "step": 320
234
+ },
235
+ {
236
+ "epoch": 10.32,
237
+ "grad_norm": 3.3187077045440674,
238
+ "learning_rate": 4.784630044641435e-06,
239
+ "loss": 0.7832,
240
+ "step": 330
241
+ },
242
+ {
243
+ "epoch": 10.64,
244
+ "grad_norm": 2.827324390411377,
245
+ "learning_rate": 4.1586894403016576e-06,
246
+ "loss": 0.7555,
247
+ "step": 340
248
+ },
249
+ {
250
+ "epoch": 10.96,
251
+ "grad_norm": 2.74627685546875,
252
+ "learning_rate": 3.565729017066729e-06,
253
+ "loss": 0.7529,
254
+ "step": 350
255
+ },
256
+ {
257
+ "epoch": 11.256,
258
+ "grad_norm": 2.8250672817230225,
259
+ "learning_rate": 3.0090966438688774e-06,
260
+ "loss": 0.6507,
261
+ "step": 360
262
+ },
263
+ {
264
+ "epoch": 11.576,
265
+ "grad_norm": 3.070279359817505,
266
+ "learning_rate": 2.491935080588658e-06,
267
+ "loss": 0.7048,
268
+ "step": 370
269
+ },
270
+ {
271
+ "epoch": 11.896,
272
+ "grad_norm": 2.929745674133301,
273
+ "learning_rate": 2.01716423395644e-06,
274
+ "loss": 0.6911,
275
+ "step": 380
276
+ },
277
+ {
278
+ "epoch": 12.192,
279
+ "grad_norm": 2.552579879760742,
280
+ "learning_rate": 1.587464671688187e-06,
281
+ "loss": 0.6039,
282
+ "step": 390
283
+ },
284
+ {
285
+ "epoch": 12.512,
286
+ "grad_norm": 2.608180046081543,
287
+ "learning_rate": 1.2052624879351105e-06,
288
+ "loss": 0.6456,
289
+ "step": 400
290
+ },
291
+ {
292
+ "epoch": 12.832,
293
+ "grad_norm": 2.6534199714660645,
294
+ "learning_rate": 8.727156054972374e-07,
295
+ "loss": 0.6479,
296
+ "step": 410
297
+ },
298
+ {
299
+ "epoch": 13.128,
300
+ "grad_norm": 2.4939088821411133,
301
+ "learning_rate": 5.917015921389569e-07,
302
+ "loss": 0.6013,
303
+ "step": 420
304
+ },
305
+ {
306
+ "epoch": 13.448,
307
+ "grad_norm": 2.7369675636291504,
308
+ "learning_rate": 3.638070597958665e-07,
309
+ "loss": 0.6168,
310
+ "step": 430
311
+ },
312
+ {
313
+ "epoch": 13.768,
314
+ "grad_norm": 2.4181711673736572,
315
+ "learning_rate": 1.903187065253076e-07,
316
+ "loss": 0.6093,
317
+ "step": 440
318
+ },
319
+ {
320
+ "epoch": 14.064,
321
+ "grad_norm": 2.7222864627838135,
322
+ "learning_rate": 7.22160517779169e-08,
323
+ "loss": 0.5911,
324
+ "step": 450
325
+ },
326
+ {
327
+ "epoch": 14.384,
328
+ "grad_norm": 2.8161678314208984,
329
+ "learning_rate": 1.0165906007056914e-08,
330
+ "loss": 0.6135,
331
+ "step": 460
332
+ }
333
+ ],
334
+ "logging_steps": 10,
335
+ "max_steps": 465,
336
+ "num_input_tokens_seen": 0,
337
+ "num_train_epochs": 15,
338
+ "save_steps": 1000,
339
+ "stateful_callbacks": {
340
+ "TrainerControl": {
341
+ "args": {
342
+ "should_epoch_stop": false,
343
+ "should_evaluate": false,
344
+ "should_log": false,
345
+ "should_save": true,
346
+ "should_training_stop": true
347
+ },
348
+ "attributes": {}
349
+ }
350
+ },
351
+ "total_flos": 1.565274744469586e+17,
352
+ "train_batch_size": 4,
353
+ "trial_name": null,
354
+ "trial_params": null
355
+ }
checkpoint-465/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7965a2214104df656922b1be16c3a7c2b84d436985ed36667de02fc406d2a34b
3
+ size 5688
checkpoint-465/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
runs/Mar15_18-19-23_3ecefcbf63c9/events.out.tfevents.1742062886.3ecefcbf63c9.153.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:153de69cb1601de25a179b8d869cccad8a7f30e09d0d0e73f70def2162e36258
3
+ size 16395
train_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
- "epoch": 24.608,
3
- "total_flos": 1.324081921088553e+17,
4
- "train_loss": 0.672794044127147,
5
- "train_runtime": 33908.1665,
6
- "train_samples_per_second": 0.369,
7
- "train_steps_per_second": 0.046
8
  }
 
1
  {
2
+ "epoch": 14.544,
3
+ "total_flos": 1.565274744469586e+17,
4
+ "train_loss": 1.4569768874875961,
5
+ "train_runtime": 22995.3507,
6
+ "train_samples_per_second": 0.652,
7
+ "train_steps_per_second": 0.02
8
  }
trainer_log.jsonl CHANGED
@@ -1,156 +1,47 @@
1
- {"current_steps": 10, "total_steps": 1550, "loss": 12.094, "lr": 9.032258064516129e-07, "epoch": 0.16, "percentage": 0.65, "elapsed_time": "0:03:37", "remaining_time": "9:17:02"}
2
- {"current_steps": 20, "total_steps": 1550, "loss": 7.0819, "lr": 2.1935483870967745e-06, "epoch": 0.32, "percentage": 1.29, "elapsed_time": "0:07:17", "remaining_time": "9:18:05"}
3
- {"current_steps": 30, "total_steps": 1550, "loss": 4.4657, "lr": 3.4838709677419357e-06, "epoch": 0.48, "percentage": 1.94, "elapsed_time": "0:10:59", "remaining_time": "9:16:32"}
4
- {"current_steps": 40, "total_steps": 1550, "loss": 3.5378, "lr": 4.774193548387097e-06, "epoch": 0.64, "percentage": 2.58, "elapsed_time": "0:14:39", "remaining_time": "9:13:35"}
5
- {"current_steps": 50, "total_steps": 1550, "loss": 2.8862, "lr": 6.064516129032259e-06, "epoch": 0.8, "percentage": 3.23, "elapsed_time": "0:18:20", "remaining_time": "9:10:16"}
6
- {"current_steps": 60, "total_steps": 1550, "loss": 2.6138, "lr": 7.35483870967742e-06, "epoch": 0.96, "percentage": 3.87, "elapsed_time": "0:22:00", "remaining_time": "9:06:40"}
7
- {"current_steps": 70, "total_steps": 1550, "loss": 2.3109, "lr": 8.64516129032258e-06, "epoch": 1.112, "percentage": 4.52, "elapsed_time": "0:25:30", "remaining_time": "8:59:25"}
8
- {"current_steps": 80, "total_steps": 1550, "loss": 2.2949, "lr": 9.935483870967742e-06, "epoch": 1.272, "percentage": 5.16, "elapsed_time": "0:29:11", "remaining_time": "8:56:15"}
9
- {"current_steps": 90, "total_steps": 1550, "loss": 2.3399, "lr": 1.1225806451612904e-05, "epoch": 1.432, "percentage": 5.81, "elapsed_time": "0:32:51", "remaining_time": "8:53:03"}
10
- {"current_steps": 100, "total_steps": 1550, "loss": 2.217, "lr": 1.2516129032258067e-05, "epoch": 1.592, "percentage": 6.45, "elapsed_time": "0:36:32", "remaining_time": "8:49:44"}
11
- {"current_steps": 110, "total_steps": 1550, "loss": 2.1938, "lr": 1.3806451612903227e-05, "epoch": 1.752, "percentage": 7.1, "elapsed_time": "0:40:12", "remaining_time": "8:46:19"}
12
- {"current_steps": 120, "total_steps": 1550, "loss": 2.0994, "lr": 1.5096774193548389e-05, "epoch": 1.912, "percentage": 7.74, "elapsed_time": "0:43:52", "remaining_time": "8:42:52"}
13
- {"current_steps": 130, "total_steps": 1550, "loss": 2.0094, "lr": 1.638709677419355e-05, "epoch": 2.064, "percentage": 8.39, "elapsed_time": "0:47:22", "remaining_time": "8:37:26"}
14
- {"current_steps": 140, "total_steps": 1550, "loss": 1.8313, "lr": 1.7677419354838713e-05, "epoch": 2.224, "percentage": 9.03, "elapsed_time": "0:51:02", "remaining_time": "8:34:03"}
15
- {"current_steps": 150, "total_steps": 1550, "loss": 1.8772, "lr": 1.896774193548387e-05, "epoch": 2.384, "percentage": 9.68, "elapsed_time": "0:54:42", "remaining_time": "8:30:39"}
16
- {"current_steps": 160, "total_steps": 1550, "loss": 1.7948, "lr": 1.9999898566691428e-05, "epoch": 2.544, "percentage": 10.32, "elapsed_time": "0:58:22", "remaining_time": "8:27:11"}
17
- {"current_steps": 170, "total_steps": 1550, "loss": 1.7994, "lr": 1.9996348616949673e-05, "epoch": 2.7039999999999997, "percentage": 10.97, "elapsed_time": "1:02:03", "remaining_time": "8:23:43"}
18
- {"current_steps": 180, "total_steps": 1550, "loss": 1.8654, "lr": 1.998772905933476e-05, "epoch": 2.864, "percentage": 11.61, "elapsed_time": "1:05:43", "remaining_time": "8:20:13"}
19
- {"current_steps": 190, "total_steps": 1550, "loss": 1.6745, "lr": 1.9974044265220564e-05, "epoch": 3.016, "percentage": 12.26, "elapsed_time": "1:09:12", "remaining_time": "8:15:25"}
20
- {"current_steps": 200, "total_steps": 1550, "loss": 1.5509, "lr": 1.995530117479521e-05, "epoch": 3.176, "percentage": 12.9, "elapsed_time": "1:12:52", "remaining_time": "8:11:56"}
21
- {"current_steps": 210, "total_steps": 1550, "loss": 1.4749, "lr": 1.993150929354139e-05, "epoch": 3.336, "percentage": 13.55, "elapsed_time": "1:16:32", "remaining_time": "8:08:26"}
22
- {"current_steps": 220, "total_steps": 1550, "loss": 1.4165, "lr": 1.9902680687415704e-05, "epoch": 3.496, "percentage": 14.19, "elapsed_time": "1:20:13", "remaining_time": "8:04:59"}
23
- {"current_steps": 230, "total_steps": 1550, "loss": 1.3226, "lr": 1.9868829976729444e-05, "epoch": 3.656, "percentage": 14.84, "elapsed_time": "1:23:54", "remaining_time": "8:01:31"}
24
- {"current_steps": 240, "total_steps": 1550, "loss": 1.5257, "lr": 1.982997432873397e-05, "epoch": 3.816, "percentage": 15.48, "elapsed_time": "1:27:34", "remaining_time": "7:58:01"}
25
- {"current_steps": 250, "total_steps": 1550, "loss": 1.4218, "lr": 1.978613344891441e-05, "epoch": 3.976, "percentage": 16.13, "elapsed_time": "1:31:15", "remaining_time": "7:54:31"}
26
- {"current_steps": 260, "total_steps": 1550, "loss": 1.2454, "lr": 1.9737329570996098e-05, "epoch": 4.128, "percentage": 16.77, "elapsed_time": "1:34:44", "remaining_time": "7:50:05"}
27
- {"current_steps": 270, "total_steps": 1550, "loss": 1.2503, "lr": 1.968358744566884e-05, "epoch": 4.288, "percentage": 17.42, "elapsed_time": "1:38:25", "remaining_time": "7:46:35"}
28
- {"current_steps": 280, "total_steps": 1550, "loss": 1.2983, "lr": 1.9624934328034673e-05, "epoch": 4.448, "percentage": 18.06, "elapsed_time": "1:42:06", "remaining_time": "7:43:05"}
29
- {"current_steps": 290, "total_steps": 1550, "loss": 1.2944, "lr": 1.9561399963785586e-05, "epoch": 4.608, "percentage": 18.71, "elapsed_time": "1:45:46", "remaining_time": "7:39:33"}
30
- {"current_steps": 300, "total_steps": 1550, "loss": 1.2997, "lr": 1.9493016574118103e-05, "epoch": 4.768, "percentage": 19.35, "elapsed_time": "1:49:26", "remaining_time": "7:36:01"}
31
- {"current_steps": 310, "total_steps": 1550, "loss": 1.2976, "lr": 1.9419818839392408e-05, "epoch": 4.928, "percentage": 20.0, "elapsed_time": "1:53:07", "remaining_time": "7:32:31"}
32
- {"current_steps": 320, "total_steps": 1550, "loss": 1.1579, "lr": 1.9341843881544372e-05, "epoch": 5.08, "percentage": 20.65, "elapsed_time": "1:56:37", "remaining_time": "7:28:17"}
33
- {"current_steps": 330, "total_steps": 1550, "loss": 1.13, "lr": 1.9259131245259293e-05, "epoch": 5.24, "percentage": 21.29, "elapsed_time": "2:00:18", "remaining_time": "7:24:47"}
34
- {"current_steps": 340, "total_steps": 1550, "loss": 1.1387, "lr": 1.917172287791698e-05, "epoch": 5.4, "percentage": 21.94, "elapsed_time": "2:03:59", "remaining_time": "7:21:15"}
35
- {"current_steps": 350, "total_steps": 1550, "loss": 1.1176, "lr": 1.9079663108318304e-05, "epoch": 5.5600000000000005, "percentage": 22.58, "elapsed_time": "2:07:40", "remaining_time": "7:17:45"}
36
- {"current_steps": 360, "total_steps": 1550, "loss": 1.1042, "lr": 1.8982998624204016e-05, "epoch": 5.72, "percentage": 23.23, "elapsed_time": "2:11:21", "remaining_time": "7:14:12"}
37
- {"current_steps": 370, "total_steps": 1550, "loss": 1.1386, "lr": 1.8881778448577274e-05, "epoch": 5.88, "percentage": 23.87, "elapsed_time": "2:15:02", "remaining_time": "7:10:40"}
38
- {"current_steps": 380, "total_steps": 1550, "loss": 0.9651, "lr": 1.877605391484179e-05, "epoch": 6.032, "percentage": 24.52, "elapsed_time": "2:18:32", "remaining_time": "7:06:32"}
39
- {"current_steps": 390, "total_steps": 1550, "loss": 0.9487, "lr": 1.8665878640768332e-05, "epoch": 6.192, "percentage": 25.16, "elapsed_time": "2:22:12", "remaining_time": "7:03:00"}
40
- {"current_steps": 400, "total_steps": 1550, "loss": 0.9193, "lr": 1.855130850130267e-05, "epoch": 6.352, "percentage": 25.81, "elapsed_time": "2:25:53", "remaining_time": "6:59:26"}
41
- {"current_steps": 410, "total_steps": 1550, "loss": 0.9112, "lr": 1.8432401600228823e-05, "epoch": 6.5120000000000005, "percentage": 26.45, "elapsed_time": "2:29:34", "remaining_time": "6:55:52"}
42
- {"current_steps": 420, "total_steps": 1550, "loss": 0.9371, "lr": 1.8309218240701973e-05, "epoch": 6.672, "percentage": 27.1, "elapsed_time": "2:33:14", "remaining_time": "6:52:18"}
43
- {"current_steps": 430, "total_steps": 1550, "loss": 1.0264, "lr": 1.818182089466595e-05, "epoch": 6.832, "percentage": 27.74, "elapsed_time": "2:36:55", "remaining_time": "6:48:45"}
44
- {"current_steps": 440, "total_steps": 1550, "loss": 0.9534, "lr": 1.8050274171170835e-05, "epoch": 6.992, "percentage": 28.39, "elapsed_time": "2:40:36", "remaining_time": "6:45:10"}
45
- {"current_steps": 450, "total_steps": 1550, "loss": 0.7345, "lr": 1.791464478360676e-05, "epoch": 7.144, "percentage": 29.03, "elapsed_time": "2:44:06", "remaining_time": "6:41:09"}
46
- {"current_steps": 460, "total_steps": 1550, "loss": 0.8399, "lr": 1.7775001515870466e-05, "epoch": 7.304, "percentage": 29.68, "elapsed_time": "2:47:47", "remaining_time": "6:37:36"}
47
- {"current_steps": 470, "total_steps": 1550, "loss": 0.7525, "lr": 1.7631415187481818e-05, "epoch": 7.464, "percentage": 30.32, "elapsed_time": "2:51:28", "remaining_time": "6:34:02"}
48
- {"current_steps": 480, "total_steps": 1550, "loss": 0.7276, "lr": 1.7483958617668e-05, "epoch": 7.624, "percentage": 30.97, "elapsed_time": "2:55:10", "remaining_time": "6:30:29"}
49
- {"current_steps": 490, "total_steps": 1550, "loss": 0.8071, "lr": 1.733270658843351e-05, "epoch": 7.784, "percentage": 31.61, "elapsed_time": "2:58:50", "remaining_time": "6:26:53"}
50
- {"current_steps": 500, "total_steps": 1550, "loss": 0.7683, "lr": 1.717773580663479e-05, "epoch": 7.944, "percentage": 32.26, "elapsed_time": "3:02:32", "remaining_time": "6:23:19"}
51
- {"current_steps": 510, "total_steps": 1550, "loss": 0.6376, "lr": 1.7019124865078625e-05, "epoch": 8.096, "percentage": 32.9, "elapsed_time": "3:06:02", "remaining_time": "6:19:22"}
52
- {"current_steps": 520, "total_steps": 1550, "loss": 0.6286, "lr": 1.6856954202664158e-05, "epoch": 8.256, "percentage": 33.55, "elapsed_time": "3:09:43", "remaining_time": "6:15:47"}
53
- {"current_steps": 530, "total_steps": 1550, "loss": 0.6196, "lr": 1.6691306063588583e-05, "epoch": 8.416, "percentage": 34.19, "elapsed_time": "3:13:23", "remaining_time": "6:12:12"}
54
- {"current_steps": 540, "total_steps": 1550, "loss": 0.564, "lr": 1.652226445563737e-05, "epoch": 8.576, "percentage": 34.84, "elapsed_time": "3:17:05", "remaining_time": "6:08:37"}
55
- {"current_steps": 550, "total_steps": 1550, "loss": 0.6122, "lr": 1.634991510758003e-05, "epoch": 8.736, "percentage": 35.48, "elapsed_time": "3:20:46", "remaining_time": "6:05:02"}
56
- {"current_steps": 560, "total_steps": 1550, "loss": 0.6173, "lr": 1.617434542569313e-05, "epoch": 8.896, "percentage": 36.13, "elapsed_time": "3:24:27", "remaining_time": "6:01:26"}
57
- {"current_steps": 570, "total_steps": 1550, "loss": 0.5342, "lr": 1.5995644449432538e-05, "epoch": 9.048, "percentage": 36.77, "elapsed_time": "3:27:57", "remaining_time": "5:57:32"}
58
- {"current_steps": 580, "total_steps": 1550, "loss": 0.4269, "lr": 1.5813902806277445e-05, "epoch": 9.208, "percentage": 37.42, "elapsed_time": "3:31:38", "remaining_time": "5:53:57"}
59
- {"current_steps": 590, "total_steps": 1550, "loss": 0.4548, "lr": 1.562921266576898e-05, "epoch": 9.368, "percentage": 38.06, "elapsed_time": "3:35:20", "remaining_time": "5:50:22"}
60
- {"current_steps": 600, "total_steps": 1550, "loss": 0.4038, "lr": 1.5441667692766805e-05, "epoch": 9.528, "percentage": 38.71, "elapsed_time": "3:39:01", "remaining_time": "5:46:47"}
61
- {"current_steps": 610, "total_steps": 1550, "loss": 0.4015, "lr": 1.5251362999947386e-05, "epoch": 9.688, "percentage": 39.35, "elapsed_time": "3:42:42", "remaining_time": "5:43:11"}
62
- {"current_steps": 620, "total_steps": 1550, "loss": 0.4353, "lr": 1.5058395099567935e-05, "epoch": 9.848, "percentage": 40.0, "elapsed_time": "3:46:23", "remaining_time": "5:39:35"}
63
- {"current_steps": 630, "total_steps": 1550, "loss": 0.3927, "lr": 1.4862861854520652e-05, "epoch": 10.0, "percentage": 40.65, "elapsed_time": "3:49:53", "remaining_time": "5:35:43"}
64
- {"current_steps": 640, "total_steps": 1550, "loss": 0.2612, "lr": 1.4664862428701925e-05, "epoch": 10.16, "percentage": 41.29, "elapsed_time": "3:53:34", "remaining_time": "5:32:06"}
65
- {"current_steps": 650, "total_steps": 1550, "loss": 0.2621, "lr": 1.4464497236721779e-05, "epoch": 10.32, "percentage": 41.94, "elapsed_time": "3:57:15", "remaining_time": "5:28:30"}
66
- {"current_steps": 660, "total_steps": 1550, "loss": 0.263, "lr": 1.4261867892979e-05, "epoch": 10.48, "percentage": 42.58, "elapsed_time": "4:00:56", "remaining_time": "5:24:54"}
67
- {"current_steps": 670, "total_steps": 1550, "loss": 0.2492, "lr": 1.4057077160127806e-05, "epoch": 10.64, "percentage": 43.23, "elapsed_time": "4:04:37", "remaining_time": "5:21:18"}
68
- {"current_steps": 680, "total_steps": 1550, "loss": 0.2523, "lr": 1.3850228896962178e-05, "epoch": 10.8, "percentage": 43.87, "elapsed_time": "4:08:18", "remaining_time": "5:17:41"}
69
- {"current_steps": 690, "total_steps": 1550, "loss": 0.2586, "lr": 1.3641428005744308e-05, "epoch": 10.96, "percentage": 44.52, "elapsed_time": "4:11:59", "remaining_time": "5:14:04"}
70
- {"current_steps": 700, "total_steps": 1550, "loss": 0.1699, "lr": 1.3430780379003814e-05, "epoch": 11.112, "percentage": 45.16, "elapsed_time": "4:15:29", "remaining_time": "5:10:14"}
71
- {"current_steps": 710, "total_steps": 1550, "loss": 0.1514, "lr": 1.3218392845834789e-05, "epoch": 11.272, "percentage": 45.81, "elapsed_time": "4:19:11", "remaining_time": "5:06:38"}
72
- {"current_steps": 720, "total_steps": 1550, "loss": 0.1432, "lr": 1.300437311771785e-05, "epoch": 11.432, "percentage": 46.45, "elapsed_time": "4:22:52", "remaining_time": "5:03:02"}
73
- {"current_steps": 730, "total_steps": 1550, "loss": 0.1512, "lr": 1.2788829733894698e-05, "epoch": 11.592, "percentage": 47.1, "elapsed_time": "4:26:34", "remaining_time": "4:59:25"}
74
- {"current_steps": 740, "total_steps": 1550, "loss": 0.1534, "lr": 1.257187200632289e-05, "epoch": 11.752, "percentage": 47.74, "elapsed_time": "4:30:15", "remaining_time": "4:55:49"}
75
- {"current_steps": 750, "total_steps": 1550, "loss": 0.1452, "lr": 1.2353609964238686e-05, "epoch": 11.912, "percentage": 48.39, "elapsed_time": "4:33:56", "remaining_time": "4:52:12"}
76
- {"current_steps": 760, "total_steps": 1550, "loss": 0.1167, "lr": 1.213415429835621e-05, "epoch": 12.064, "percentage": 49.03, "elapsed_time": "4:37:26", "remaining_time": "4:48:24"}
77
- {"current_steps": 770, "total_steps": 1550, "loss": 0.0785, "lr": 1.1913616304731064e-05, "epoch": 12.224, "percentage": 49.68, "elapsed_time": "4:41:07", "remaining_time": "4:44:46"}
78
- {"current_steps": 780, "total_steps": 1550, "loss": 0.0857, "lr": 1.1692107828317014e-05, "epoch": 12.384, "percentage": 50.32, "elapsed_time": "4:44:48", "remaining_time": "4:41:09"}
79
- {"current_steps": 790, "total_steps": 1550, "loss": 0.0862, "lr": 1.1469741206244249e-05, "epoch": 12.544, "percentage": 50.97, "elapsed_time": "4:48:29", "remaining_time": "4:37:32"}
80
- {"current_steps": 800, "total_steps": 1550, "loss": 0.0949, "lr": 1.1246629210848062e-05, "epoch": 12.704, "percentage": 51.61, "elapsed_time": "4:52:10", "remaining_time": "4:33:54"}
81
- {"current_steps": 810, "total_steps": 1550, "loss": 0.0928, "lr": 1.1022884992476826e-05, "epoch": 12.864, "percentage": 52.26, "elapsed_time": "4:55:51", "remaining_time": "4:30:17"}
82
- {"current_steps": 820, "total_steps": 1550, "loss": 0.0951, "lr": 1.0821068423364156e-05, "epoch": 13.016, "percentage": 52.9, "elapsed_time": "4:59:21", "remaining_time": "4:26:30"}
83
- {"current_steps": 830, "total_steps": 1550, "loss": 0.0483, "lr": 1.0596435812513276e-05, "epoch": 13.176, "percentage": 53.55, "elapsed_time": "5:03:01", "remaining_time": "4:22:52"}
84
- {"current_steps": 840, "total_steps": 1550, "loss": 0.0559, "lr": 1.037150072164626e-05, "epoch": 13.336, "percentage": 54.19, "elapsed_time": "5:06:42", "remaining_time": "4:19:14"}
85
- {"current_steps": 850, "total_steps": 1550, "loss": 0.0801, "lr": 1.0146377225686996e-05, "epoch": 13.496, "percentage": 54.84, "elapsed_time": "5:10:23", "remaining_time": "4:15:36"}
86
- {"current_steps": 860, "total_steps": 1550, "loss": 0.0683, "lr": 9.921179495108249e-06, "epoch": 13.656, "percentage": 55.48, "elapsed_time": "5:14:03", "remaining_time": "4:11:58"}
87
- {"current_steps": 870, "total_steps": 1550, "loss": 0.0616, "lr": 9.696021738030575e-06, "epoch": 13.816, "percentage": 56.13, "elapsed_time": "5:17:44", "remaining_time": "4:08:21"}
88
- {"current_steps": 880, "total_steps": 1550, "loss": 0.058, "lr": 9.471018142302127e-06, "epoch": 13.975999999999999, "percentage": 56.77, "elapsed_time": "5:21:25", "remaining_time": "4:04:42"}
89
- {"current_steps": 890, "total_steps": 1550, "loss": 0.0356, "lr": 9.24628281758876e-06, "epoch": 14.128, "percentage": 57.42, "elapsed_time": "5:24:54", "remaining_time": "4:00:56"}
90
- {"current_steps": 900, "total_steps": 1550, "loss": 0.0458, "lr": 9.021929737503757e-06, "epoch": 14.288, "percentage": 58.06, "elapsed_time": "5:28:34", "remaining_time": "3:57:18"}
91
- {"current_steps": 910, "total_steps": 1550, "loss": 0.0531, "lr": 8.79807268180658e-06, "epoch": 14.448, "percentage": 58.71, "elapsed_time": "5:32:15", "remaining_time": "3:53:40"}
92
- {"current_steps": 920, "total_steps": 1550, "loss": 0.0359, "lr": 8.574825178699935e-06, "epoch": 14.608, "percentage": 59.35, "elapsed_time": "5:35:55", "remaining_time": "3:50:02"}
93
- {"current_steps": 930, "total_steps": 1550, "loss": 0.0362, "lr": 8.352300447254372e-06, "epoch": 14.768, "percentage": 60.0, "elapsed_time": "5:39:36", "remaining_time": "3:46:24"}
94
- {"current_steps": 940, "total_steps": 1550, "loss": 0.0292, "lr": 8.130611339989731e-06, "epoch": 14.928, "percentage": 60.65, "elapsed_time": "5:43:16", "remaining_time": "3:42:45"}
95
- {"current_steps": 950, "total_steps": 1550, "loss": 0.0241, "lr": 7.909870285642403e-06, "epoch": 15.08, "percentage": 61.29, "elapsed_time": "5:46:45", "remaining_time": "3:39:00"}
96
- {"current_steps": 960, "total_steps": 1550, "loss": 0.0264, "lr": 7.690189232147566e-06, "epoch": 15.24, "percentage": 61.94, "elapsed_time": "5:50:26", "remaining_time": "3:35:22"}
97
- {"current_steps": 970, "total_steps": 1550, "loss": 0.0231, "lr": 7.4716795898652615e-06, "epoch": 15.4, "percentage": 62.58, "elapsed_time": "5:54:06", "remaining_time": "3:31:44"}
98
- {"current_steps": 980, "total_steps": 1550, "loss": 0.0243, "lr": 7.2544521750790345e-06, "epoch": 15.56, "percentage": 63.23, "elapsed_time": "5:57:46", "remaining_time": "3:28:05"}
99
- {"current_steps": 990, "total_steps": 1550, "loss": 0.0226, "lr": 7.038617153795948e-06, "epoch": 15.72, "percentage": 63.87, "elapsed_time": "6:01:27", "remaining_time": "3:24:27"}
100
- {"current_steps": 1000, "total_steps": 1550, "loss": 0.0321, "lr": 6.82428398587631e-06, "epoch": 15.88, "percentage": 64.52, "elapsed_time": "6:05:07", "remaining_time": "3:20:48"}
101
- {"current_steps": 1010, "total_steps": 1550, "loss": 0.019, "lr": 6.611561369521546e-06, "epoch": 16.032, "percentage": 65.16, "elapsed_time": "6:08:38", "remaining_time": "3:17:05"}
102
- {"current_steps": 1020, "total_steps": 1550, "loss": 0.0101, "lr": 6.400557186148371e-06, "epoch": 16.192, "percentage": 65.81, "elapsed_time": "6:12:18", "remaining_time": "3:13:27"}
103
- {"current_steps": 1030, "total_steps": 1550, "loss": 0.0139, "lr": 6.191378445677125e-06, "epoch": 16.352, "percentage": 66.45, "elapsed_time": "6:15:58", "remaining_time": "3:09:48"}
104
- {"current_steps": 1040, "total_steps": 1550, "loss": 0.0264, "lr": 5.984131232262167e-06, "epoch": 16.512, "percentage": 67.1, "elapsed_time": "6:19:39", "remaining_time": "3:06:10"}
105
- {"current_steps": 1050, "total_steps": 1550, "loss": 0.0123, "lr": 5.7789206504916815e-06, "epoch": 16.672, "percentage": 67.74, "elapsed_time": "6:23:19", "remaining_time": "3:02:32"}
106
- {"current_steps": 1060, "total_steps": 1550, "loss": 0.0115, "lr": 5.5758507720843425e-06, "epoch": 16.832, "percentage": 68.39, "elapsed_time": "6:26:59", "remaining_time": "2:58:53"}
107
- {"current_steps": 1070, "total_steps": 1550, "loss": 0.0135, "lr": 5.375024583109745e-06, "epoch": 16.992, "percentage": 69.03, "elapsed_time": "6:30:39", "remaining_time": "2:55:14"}
108
- {"current_steps": 1080, "total_steps": 1550, "loss": 0.005, "lr": 5.176543931759447e-06, "epoch": 17.144, "percentage": 69.68, "elapsed_time": "6:34:08", "remaining_time": "2:51:31"}
109
- {"current_steps": 1090, "total_steps": 1550, "loss": 0.0096, "lr": 4.980509476695043e-06, "epoch": 17.304, "percentage": 70.32, "elapsed_time": "6:37:48", "remaining_time": "2:47:52"}
110
- {"current_steps": 1100, "total_steps": 1550, "loss": 0.0148, "lr": 4.7870206359995815e-06, "epoch": 17.464, "percentage": 70.97, "elapsed_time": "6:41:28", "remaining_time": "2:44:14"}
111
- {"current_steps": 1110, "total_steps": 1550, "loss": 0.0067, "lr": 4.596175536758024e-06, "epoch": 17.624, "percentage": 71.61, "elapsed_time": "6:45:08", "remaining_time": "2:40:35"}
112
- {"current_steps": 1120, "total_steps": 1550, "loss": 0.0053, "lr": 4.408070965292534e-06, "epoch": 17.784, "percentage": 72.26, "elapsed_time": "6:48:52", "remaining_time": "2:36:58"}
113
- {"current_steps": 1130, "total_steps": 1550, "loss": 0.0079, "lr": 4.222802318077664e-06, "epoch": 17.944, "percentage": 72.9, "elapsed_time": "6:52:31", "remaining_time": "2:33:19"}
114
- {"current_steps": 1140, "total_steps": 1550, "loss": 0.0039, "lr": 4.040463553360431e-06, "epoch": 18.096, "percentage": 73.55, "elapsed_time": "6:56:00", "remaining_time": "2:29:37"}
115
- {"current_steps": 1150, "total_steps": 1550, "loss": 0.0023, "lr": 3.861147143509754e-06, "epoch": 18.256, "percentage": 74.19, "elapsed_time": "6:59:40", "remaining_time": "2:25:58"}
116
- {"current_steps": 1160, "total_steps": 1550, "loss": 0.006, "lr": 3.6849440281194813e-06, "epoch": 18.416, "percentage": 74.84, "elapsed_time": "7:03:19", "remaining_time": "2:22:19"}
117
- {"current_steps": 1170, "total_steps": 1550, "loss": 0.0023, "lr": 3.5119435678887328e-06, "epoch": 18.576, "percentage": 75.48, "elapsed_time": "7:06:59", "remaining_time": "2:18:40"}
118
- {"current_steps": 1180, "total_steps": 1550, "loss": 0.003, "lr": 3.342233499302985e-06, "epoch": 18.736, "percentage": 76.13, "elapsed_time": "7:10:39", "remaining_time": "2:15:02"}
119
- {"current_steps": 1190, "total_steps": 1550, "loss": 0.002, "lr": 3.175899890138858e-06, "epoch": 18.896, "percentage": 76.77, "elapsed_time": "7:14:19", "remaining_time": "2:11:23"}
120
- {"current_steps": 1200, "total_steps": 1550, "loss": 0.0022, "lr": 3.0130270958152196e-06, "epoch": 19.048, "percentage": 77.42, "elapsed_time": "7:17:47", "remaining_time": "2:07:41"}
121
- {"current_steps": 1210, "total_steps": 1550, "loss": 0.0022, "lr": 2.8536977166126234e-06, "epoch": 19.208, "percentage": 78.06, "elapsed_time": "7:21:27", "remaining_time": "2:04:02"}
122
- {"current_steps": 1220, "total_steps": 1550, "loss": 0.0016, "lr": 2.697992555782969e-06, "epoch": 19.368, "percentage": 78.71, "elapsed_time": "7:25:07", "remaining_time": "2:00:24"}
123
- {"current_steps": 1230, "total_steps": 1550, "loss": 0.0015, "lr": 2.545990578570404e-06, "epoch": 19.528, "percentage": 79.35, "elapsed_time": "7:28:47", "remaining_time": "1:56:45"}
124
- {"current_steps": 1240, "total_steps": 1550, "loss": 0.0018, "lr": 2.397768872164462e-06, "epoch": 19.688, "percentage": 80.0, "elapsed_time": "7:32:26", "remaining_time": "1:53:06"}
125
- {"current_steps": 1250, "total_steps": 1550, "loss": 0.0014, "lr": 2.253402606605577e-06, "epoch": 19.848, "percentage": 80.65, "elapsed_time": "7:36:06", "remaining_time": "1:49:27"}
126
- {"current_steps": 1260, "total_steps": 1550, "loss": 0.0013, "lr": 2.1129649966629185e-06, "epoch": 20.0, "percentage": 81.29, "elapsed_time": "7:39:34", "remaining_time": "1:45:46"}
127
- {"current_steps": 1270, "total_steps": 1550, "loss": 0.0013, "lr": 1.9765272647038038e-06, "epoch": 20.16, "percentage": 81.94, "elapsed_time": "7:43:14", "remaining_time": "1:42:07"}
128
- {"current_steps": 1280, "total_steps": 1550, "loss": 0.0011, "lr": 1.8441586045735737e-06, "epoch": 20.32, "percentage": 82.58, "elapsed_time": "7:46:54", "remaining_time": "1:38:29"}
129
- {"current_steps": 1290, "total_steps": 1550, "loss": 0.0013, "lr": 1.7159261465041954e-06, "epoch": 20.48, "percentage": 83.23, "elapsed_time": "7:50:33", "remaining_time": "1:34:50"}
130
- {"current_steps": 1300, "total_steps": 1550, "loss": 0.0014, "lr": 1.5918949230694635e-06, "epoch": 20.64, "percentage": 83.87, "elapsed_time": "7:54:13", "remaining_time": "1:31:11"}
131
- {"current_steps": 1310, "total_steps": 1550, "loss": 0.0011, "lr": 1.4721278362039626e-06, "epoch": 20.8, "percentage": 84.52, "elapsed_time": "7:57:53", "remaining_time": "1:27:33"}
132
- {"current_steps": 1320, "total_steps": 1550, "loss": 0.0012, "lr": 1.356685625302625e-06, "epoch": 20.96, "percentage": 85.16, "elapsed_time": "8:01:33", "remaining_time": "1:23:54"}
133
- {"current_steps": 1330, "total_steps": 1550, "loss": 0.0011, "lr": 1.2456268364169853e-06, "epoch": 21.112, "percentage": 85.81, "elapsed_time": "8:05:01", "remaining_time": "1:20:13"}
134
- {"current_steps": 1340, "total_steps": 1550, "loss": 0.0011, "lr": 1.1390077925637865e-06, "epoch": 21.272, "percentage": 86.45, "elapsed_time": "8:08:41", "remaining_time": "1:16:35"}
135
- {"current_steps": 1350, "total_steps": 1550, "loss": 0.001, "lr": 1.0368825651609893e-06, "epoch": 21.432, "percentage": 87.1, "elapsed_time": "8:12:20", "remaining_time": "1:12:56"}
136
- {"current_steps": 1360, "total_steps": 1550, "loss": 0.0012, "lr": 9.393029466056714e-07, "epoch": 21.592, "percentage": 87.74, "elapsed_time": "8:16:00", "remaining_time": "1:09:17"}
137
- {"current_steps": 1370, "total_steps": 1550, "loss": 0.0012, "lr": 8.463184240077172e-07, "epoch": 21.752, "percentage": 88.39, "elapsed_time": "8:19:40", "remaining_time": "1:05:39"}
138
- {"current_steps": 1380, "total_steps": 1550, "loss": 0.0011, "lr": 7.579761540926434e-07, "epoch": 21.912, "percentage": 89.03, "elapsed_time": "8:23:20", "remaining_time": "1:02:00"}
139
- {"current_steps": 1390, "total_steps": 1550, "loss": 0.001, "lr": 6.743209392862349e-07, "epoch": 22.064, "percentage": 89.68, "elapsed_time": "8:26:48", "remaining_time": "0:58:20"}
140
- {"current_steps": 1400, "total_steps": 1550, "loss": 0.0011, "lr": 5.953952049931999e-07, "epoch": 22.224, "percentage": 90.32, "elapsed_time": "8:30:28", "remaining_time": "0:54:41"}
141
- {"current_steps": 1410, "total_steps": 1550, "loss": 0.001, "lr": 5.212389780812733e-07, "epoch": 22.384, "percentage": 90.97, "elapsed_time": "8:34:08", "remaining_time": "0:51:02"}
142
- {"current_steps": 1420, "total_steps": 1550, "loss": 0.0011, "lr": 4.518898665817695e-07, "epoch": 22.544, "percentage": 91.61, "elapsed_time": "8:37:48", "remaining_time": "0:47:24"}
143
- {"current_steps": 1430, "total_steps": 1550, "loss": 0.0011, "lr": 3.8738304061681107e-07, "epoch": 22.704, "percentage": 92.26, "elapsed_time": "8:41:27", "remaining_time": "0:43:45"}
144
- {"current_steps": 1440, "total_steps": 1550, "loss": 0.0011, "lr": 3.2775121456295024e-07, "epoch": 22.864, "percentage": 92.9, "elapsed_time": "8:45:07", "remaining_time": "0:40:06"}
145
- {"current_steps": 1450, "total_steps": 1550, "loss": 0.001, "lr": 2.730246304601991e-07, "epoch": 23.016, "percentage": 93.55, "elapsed_time": "8:48:36", "remaining_time": "0:36:27"}
146
- {"current_steps": 1460, "total_steps": 1550, "loss": 0.0011, "lr": 2.2323104267490404e-07, "epoch": 23.176, "percentage": 94.19, "elapsed_time": "8:52:16", "remaining_time": "0:32:48"}
147
- {"current_steps": 1470, "total_steps": 1550, "loss": 0.001, "lr": 1.783957038242279e-07, "epoch": 23.336, "percentage": 94.84, "elapsed_time": "8:55:56", "remaining_time": "0:29:10"}
148
- {"current_steps": 1480, "total_steps": 1550, "loss": 0.001, "lr": 1.3854135196939345e-07, "epoch": 23.496, "percentage": 95.48, "elapsed_time": "8:59:36", "remaining_time": "0:25:31"}
149
- {"current_steps": 1490, "total_steps": 1550, "loss": 0.0011, "lr": 1.0368819908415983e-07, "epoch": 23.656, "percentage": 96.13, "elapsed_time": "9:03:15", "remaining_time": "0:21:52"}
150
- {"current_steps": 1500, "total_steps": 1550, "loss": 0.0011, "lr": 7.385392080440535e-08, "epoch": 23.816, "percentage": 96.77, "elapsed_time": "9:06:55", "remaining_time": "0:18:13"}
151
- {"current_steps": 1510, "total_steps": 1550, "loss": 0.0011, "lr": 4.905364746400021e-08, "epoch": 23.976, "percentage": 97.42, "elapsed_time": "9:10:35", "remaining_time": "0:14:35"}
152
- {"current_steps": 1520, "total_steps": 1550, "loss": 0.001, "lr": 2.929995642151906e-08, "epoch": 24.128, "percentage": 98.06, "elapsed_time": "9:14:04", "remaining_time": "0:10:56"}
153
- {"current_steps": 1530, "total_steps": 1550, "loss": 0.001, "lr": 1.4602865681682122e-08, "epoch": 24.288, "percentage": 98.71, "elapsed_time": "9:17:43", "remaining_time": "0:07:17"}
154
- {"current_steps": 1540, "total_steps": 1550, "loss": 0.001, "lr": 4.969828814767042e-09, "epoch": 24.448, "percentage": 99.35, "elapsed_time": "9:21:23", "remaining_time": "0:03:38"}
155
- {"current_steps": 1550, "total_steps": 1550, "loss": 0.001, "lr": 4.0573117655595684e-10, "epoch": 24.608, "percentage": 100.0, "elapsed_time": "9:25:03", "remaining_time": "0:00:00"}
156
- {"current_steps": 1550, "total_steps": 1550, "epoch": 24.608, "percentage": 100.0, "elapsed_time": "9:25:06", "remaining_time": "0:00:00"}
 
1
+ {"current_steps": 10, "total_steps": 465, "loss": 10.0348, "lr": 3.8297872340425535e-06, "epoch": 0.32, "percentage": 2.15, "elapsed_time": "0:08:22", "remaining_time": "6:21:23"}
2
+ {"current_steps": 20, "total_steps": 465, "loss": 4.7312, "lr": 8.085106382978723e-06, "epoch": 0.64, "percentage": 4.3, "elapsed_time": "0:16:48", "remaining_time": "6:14:03"}
3
+ {"current_steps": 30, "total_steps": 465, "loss": 3.4362, "lr": 1.2340425531914895e-05, "epoch": 0.96, "percentage": 6.45, "elapsed_time": "0:25:14", "remaining_time": "6:05:54"}
4
+ {"current_steps": 40, "total_steps": 465, "loss": 2.5739, "lr": 1.6595744680851064e-05, "epoch": 1.256, "percentage": 8.6, "elapsed_time": "0:33:01", "remaining_time": "5:50:50"}
5
+ {"current_steps": 50, "total_steps": 465, "loss": 2.4828, "lr": 1.9998870284726968e-05, "epoch": 1.576, "percentage": 10.75, "elapsed_time": "0:41:27", "remaining_time": "5:44:04"}
6
+ {"current_steps": 60, "total_steps": 465, "loss": 2.1904, "lr": 1.9959357045100764e-05, "epoch": 1.896, "percentage": 12.9, "elapsed_time": "0:49:52", "remaining_time": "5:36:37"}
7
+ {"current_steps": 70, "total_steps": 465, "loss": 1.893, "lr": 1.9863613034027224e-05, "epoch": 2.192, "percentage": 15.05, "elapsed_time": "0:57:38", "remaining_time": "5:25:18"}
8
+ {"current_steps": 80, "total_steps": 465, "loss": 1.9328, "lr": 1.971217882451521e-05, "epoch": 2.512, "percentage": 17.2, "elapsed_time": "1:06:04", "remaining_time": "5:17:56"}
9
+ {"current_steps": 90, "total_steps": 465, "loss": 1.8361, "lr": 1.9505909417784758e-05, "epoch": 2.832, "percentage": 19.35, "elapsed_time": "1:14:29", "remaining_time": "5:10:22"}
10
+ {"current_steps": 100, "total_steps": 465, "loss": 1.6677, "lr": 1.9245969415909464e-05, "epoch": 3.128, "percentage": 21.51, "elapsed_time": "1:22:16", "remaining_time": "5:00:19"}
11
+ {"current_steps": 110, "total_steps": 465, "loss": 1.7492, "lr": 1.8933826446444933e-05, "epoch": 3.448, "percentage": 23.66, "elapsed_time": "1:30:41", "remaining_time": "4:52:41"}
12
+ {"current_steps": 120, "total_steps": 465, "loss": 1.6435, "lr": 1.8571242876167995e-05, "epoch": 3.768, "percentage": 25.81, "elapsed_time": "1:39:07", "remaining_time": "4:44:58"}
13
+ {"current_steps": 130, "total_steps": 465, "loss": 1.478, "lr": 1.8160265860711134e-05, "epoch": 4.064, "percentage": 27.96, "elapsed_time": "1:46:54", "remaining_time": "4:35:28"}
14
+ {"current_steps": 140, "total_steps": 465, "loss": 1.4807, "lr": 1.770321578627213e-05, "epoch": 4.384, "percentage": 30.11, "elapsed_time": "1:55:19", "remaining_time": "4:27:42"}
15
+ {"current_steps": 150, "total_steps": 465, "loss": 1.375, "lr": 1.7202673168657318e-05, "epoch": 4.704, "percentage": 32.26, "elapsed_time": "2:03:44", "remaining_time": "4:19:50"}
16
+ {"current_steps": 160, "total_steps": 465, "loss": 1.2751, "lr": 1.6661464083626734e-05, "epoch": 5.0, "percentage": 34.41, "elapsed_time": "2:11:32", "remaining_time": "4:10:45"}
17
+ {"current_steps": 170, "total_steps": 465, "loss": 1.2887, "lr": 1.6082644210801846e-05, "epoch": 5.32, "percentage": 36.56, "elapsed_time": "2:19:58", "remaining_time": "4:02:54"}
18
+ {"current_steps": 180, "total_steps": 465, "loss": 1.2852, "lr": 1.5469481581224274e-05, "epoch": 5.64, "percentage": 38.71, "elapsed_time": "2:28:24", "remaining_time": "3:54:58"}
19
+ {"current_steps": 190, "total_steps": 465, "loss": 1.2329, "lr": 1.4825438125973263e-05, "epoch": 5.96, "percentage": 40.86, "elapsed_time": "2:36:50", "remaining_time": "3:47:00"}
20
+ {"current_steps": 200, "total_steps": 465, "loss": 1.1001, "lr": 1.4154150130018867e-05, "epoch": 6.256, "percentage": 43.01, "elapsed_time": "2:44:37", "remaining_time": "3:38:08"}
21
+ {"current_steps": 210, "total_steps": 465, "loss": 1.1543, "lr": 1.3459407701668762e-05, "epoch": 6.576, "percentage": 45.16, "elapsed_time": "2:53:01", "remaining_time": "3:30:06"}
22
+ {"current_steps": 220, "total_steps": 465, "loss": 1.132, "lr": 1.2745133373524855e-05, "epoch": 6.896, "percentage": 47.31, "elapsed_time": "3:01:28", "remaining_time": "3:22:05"}
23
+ {"current_steps": 230, "total_steps": 465, "loss": 1.0284, "lr": 1.2015359955769021e-05, "epoch": 7.192, "percentage": 49.46, "elapsed_time": "3:09:16", "remaining_time": "3:13:23"}
24
+ {"current_steps": 240, "total_steps": 465, "loss": 1.0392, "lr": 1.127420776681905e-05, "epoch": 7.5120000000000005, "percentage": 51.61, "elapsed_time": "3:17:42", "remaining_time": "3:05:21"}
25
+ {"current_steps": 250, "total_steps": 465, "loss": 1.0436, "lr": 1.0525861369910877e-05, "epoch": 7.832, "percentage": 53.76, "elapsed_time": "3:26:09", "remaining_time": "2:57:17"}
26
+ {"current_steps": 260, "total_steps": 465, "loss": 0.8973, "lr": 9.77454594695308e-06, "epoch": 8.128, "percentage": 55.91, "elapsed_time": "3:33:57", "remaining_time": "2:48:41"}
27
+ {"current_steps": 270, "total_steps": 465, "loss": 0.9455, "lr": 9.024503443047318e-06, "epoch": 8.448, "percentage": 58.06, "elapsed_time": "3:42:23", "remaining_time": "2:40:37"}
28
+ {"current_steps": 280, "total_steps": 465, "loss": 0.9297, "lr": 8.279968616363417e-06, "epoch": 8.768, "percentage": 60.22, "elapsed_time": "3:50:50", "remaining_time": "2:32:31"}
29
+ {"current_steps": 290, "total_steps": 465, "loss": 0.8414, "lr": 7.545145128592009e-06, "epoch": 9.064, "percentage": 62.37, "elapsed_time": "3:58:39", "remaining_time": "2:24:00"}
30
+ {"current_steps": 300, "total_steps": 465, "loss": 0.8513, "lr": 6.824181810968675e-06, "epoch": 9.384, "percentage": 64.52, "elapsed_time": "4:07:04", "remaining_time": "2:15:53"}
31
+ {"current_steps": 310, "total_steps": 465, "loss": 0.8351, "lr": 6.121149239872151e-06, "epoch": 9.704, "percentage": 66.67, "elapsed_time": "4:15:31", "remaining_time": "2:07:45"}
32
+ {"current_steps": 320, "total_steps": 465, "loss": 0.7886, "lr": 5.440016754251364e-06, "epoch": 10.0, "percentage": 68.82, "elapsed_time": "4:23:20", "remaining_time": "1:59:19"}
33
+ {"current_steps": 330, "total_steps": 465, "loss": 0.7832, "lr": 4.784630044641435e-06, "epoch": 10.32, "percentage": 70.97, "elapsed_time": "4:31:47", "remaining_time": "1:51:11"}
34
+ {"current_steps": 340, "total_steps": 465, "loss": 0.7555, "lr": 4.1586894403016576e-06, "epoch": 10.64, "percentage": 73.12, "elapsed_time": "4:40:13", "remaining_time": "1:43:01"}
35
+ {"current_steps": 350, "total_steps": 465, "loss": 0.7529, "lr": 3.565729017066729e-06, "epoch": 10.96, "percentage": 75.27, "elapsed_time": "4:48:39", "remaining_time": "1:34:50"}
36
+ {"current_steps": 360, "total_steps": 465, "loss": 0.6507, "lr": 3.0090966438688774e-06, "epoch": 11.256, "percentage": 77.42, "elapsed_time": "4:56:29", "remaining_time": "1:26:28"}
37
+ {"current_steps": 370, "total_steps": 465, "loss": 0.7048, "lr": 2.491935080588658e-06, "epoch": 11.576, "percentage": 79.57, "elapsed_time": "5:04:56", "remaining_time": "1:18:17"}
38
+ {"current_steps": 380, "total_steps": 465, "loss": 0.6911, "lr": 2.01716423395644e-06, "epoch": 11.896, "percentage": 81.72, "elapsed_time": "5:13:22", "remaining_time": "1:10:05"}
39
+ {"current_steps": 390, "total_steps": 465, "loss": 0.6039, "lr": 1.587464671688187e-06, "epoch": 12.192, "percentage": 83.87, "elapsed_time": "5:21:10", "remaining_time": "1:01:45"}
40
+ {"current_steps": 400, "total_steps": 465, "loss": 0.6456, "lr": 1.2052624879351105e-06, "epoch": 12.512, "percentage": 86.02, "elapsed_time": "5:29:36", "remaining_time": "0:53:33"}
41
+ {"current_steps": 410, "total_steps": 465, "loss": 0.6479, "lr": 8.727156054972374e-07, "epoch": 12.832, "percentage": 88.17, "elapsed_time": "5:38:02", "remaining_time": "0:45:20"}
42
+ {"current_steps": 420, "total_steps": 465, "loss": 0.6013, "lr": 5.917015921389569e-07, "epoch": 13.128, "percentage": 90.32, "elapsed_time": "5:45:51", "remaining_time": "0:37:03"}
43
+ {"current_steps": 430, "total_steps": 465, "loss": 0.6168, "lr": 3.638070597958665e-07, "epoch": 13.448, "percentage": 92.47, "elapsed_time": "5:54:19", "remaining_time": "0:28:50"}
44
+ {"current_steps": 440, "total_steps": 465, "loss": 0.6093, "lr": 1.903187065253076e-07, "epoch": 13.768, "percentage": 94.62, "elapsed_time": "6:02:46", "remaining_time": "0:20:36"}
45
+ {"current_steps": 450, "total_steps": 465, "loss": 0.5911, "lr": 7.22160517779169e-08, "epoch": 14.064, "percentage": 96.77, "elapsed_time": "6:10:33", "remaining_time": "0:12:21"}
46
+ {"current_steps": 460, "total_steps": 465, "loss": 0.6135, "lr": 1.0165906007056914e-08, "epoch": 14.384, "percentage": 98.92, "elapsed_time": "6:18:59", "remaining_time": "0:04:07"}
47
+ {"current_steps": 465, "total_steps": 465, "epoch": 14.544, "percentage": 100.0, "elapsed_time": "6:23:14", "remaining_time": "0:00:00"}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
trainer_state.json CHANGED
@@ -1,1112 +1,349 @@
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
- "epoch": 24.608,
5
  "eval_steps": 500,
6
- "global_step": 1550,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
- "epoch": 0.16,
13
- "grad_norm": 155.76007080078125,
14
- "learning_rate": 9.032258064516129e-07,
15
- "loss": 12.094,
16
  "step": 10
17
  },
18
  {
19
- "epoch": 0.32,
20
- "grad_norm": 37.119384765625,
21
- "learning_rate": 2.1935483870967745e-06,
22
- "loss": 7.0819,
23
  "step": 20
24
  },
25
  {
26
- "epoch": 0.48,
27
- "grad_norm": 14.752822875976562,
28
- "learning_rate": 3.4838709677419357e-06,
29
- "loss": 4.4657,
30
  "step": 30
31
  },
32
  {
33
- "epoch": 0.64,
34
- "grad_norm": 11.597710609436035,
35
- "learning_rate": 4.774193548387097e-06,
36
- "loss": 3.5378,
37
  "step": 40
38
  },
39
  {
40
- "epoch": 0.8,
41
- "grad_norm": 15.393077850341797,
42
- "learning_rate": 6.064516129032259e-06,
43
- "loss": 2.8862,
44
  "step": 50
45
  },
46
  {
47
- "epoch": 0.96,
48
- "grad_norm": 23.84307861328125,
49
- "learning_rate": 7.35483870967742e-06,
50
- "loss": 2.6138,
51
  "step": 60
52
  },
53
  {
54
- "epoch": 1.112,
55
- "grad_norm": 13.163668632507324,
56
- "learning_rate": 8.64516129032258e-06,
57
- "loss": 2.3109,
58
  "step": 70
59
  },
60
  {
61
- "epoch": 1.272,
62
- "grad_norm": 12.168913841247559,
63
- "learning_rate": 9.935483870967742e-06,
64
- "loss": 2.2949,
65
  "step": 80
66
  },
67
  {
68
- "epoch": 1.432,
69
- "grad_norm": 10.725199699401855,
70
- "learning_rate": 1.1225806451612904e-05,
71
- "loss": 2.3399,
72
  "step": 90
73
  },
74
  {
75
- "epoch": 1.592,
76
- "grad_norm": 8.531355857849121,
77
- "learning_rate": 1.2516129032258067e-05,
78
- "loss": 2.217,
79
  "step": 100
80
  },
81
  {
82
- "epoch": 1.752,
83
- "grad_norm": 6.670936584472656,
84
- "learning_rate": 1.3806451612903227e-05,
85
- "loss": 2.1938,
86
  "step": 110
87
  },
88
  {
89
- "epoch": 1.912,
90
- "grad_norm": 5.666457653045654,
91
- "learning_rate": 1.5096774193548389e-05,
92
- "loss": 2.0994,
93
  "step": 120
94
  },
95
  {
96
- "epoch": 2.064,
97
- "grad_norm": 7.0824384689331055,
98
- "learning_rate": 1.638709677419355e-05,
99
- "loss": 2.0094,
100
  "step": 130
101
  },
102
  {
103
- "epoch": 2.224,
104
- "grad_norm": 5.3269195556640625,
105
- "learning_rate": 1.7677419354838713e-05,
106
- "loss": 1.8313,
107
  "step": 140
108
  },
109
  {
110
- "epoch": 2.384,
111
- "grad_norm": 3.4799787998199463,
112
- "learning_rate": 1.896774193548387e-05,
113
- "loss": 1.8772,
114
  "step": 150
115
  },
116
  {
117
- "epoch": 2.544,
118
- "grad_norm": 4.512059211730957,
119
- "learning_rate": 1.9999898566691428e-05,
120
- "loss": 1.7948,
121
  "step": 160
122
  },
123
  {
124
- "epoch": 2.7039999999999997,
125
- "grad_norm": 9.884415626525879,
126
- "learning_rate": 1.9996348616949673e-05,
127
- "loss": 1.7994,
128
  "step": 170
129
  },
130
  {
131
- "epoch": 2.864,
132
- "grad_norm": 3.1838889122009277,
133
- "learning_rate": 1.998772905933476e-05,
134
- "loss": 1.8654,
135
  "step": 180
136
  },
137
  {
138
- "epoch": 3.016,
139
- "grad_norm": 3.452301263809204,
140
- "learning_rate": 1.9974044265220564e-05,
141
- "loss": 1.6745,
142
  "step": 190
143
  },
144
  {
145
- "epoch": 3.176,
146
- "grad_norm": 3.3805224895477295,
147
- "learning_rate": 1.995530117479521e-05,
148
- "loss": 1.5509,
149
  "step": 200
150
  },
151
  {
152
- "epoch": 3.336,
153
- "grad_norm": 6.541603088378906,
154
- "learning_rate": 1.993150929354139e-05,
155
- "loss": 1.4749,
156
  "step": 210
157
  },
158
  {
159
- "epoch": 3.496,
160
- "grad_norm": 2.95489764213562,
161
- "learning_rate": 1.9902680687415704e-05,
162
- "loss": 1.4165,
163
  "step": 220
164
  },
165
  {
166
- "epoch": 3.656,
167
- "grad_norm": 3.144228458404541,
168
- "learning_rate": 1.9868829976729444e-05,
169
- "loss": 1.3226,
170
  "step": 230
171
  },
172
  {
173
- "epoch": 3.816,
174
- "grad_norm": 3.747593641281128,
175
- "learning_rate": 1.982997432873397e-05,
176
- "loss": 1.5257,
177
  "step": 240
178
  },
179
  {
180
- "epoch": 3.976,
181
- "grad_norm": 2.2221176624298096,
182
- "learning_rate": 1.978613344891441e-05,
183
- "loss": 1.4218,
184
  "step": 250
185
  },
186
  {
187
- "epoch": 4.128,
188
- "grad_norm": 2.854719877243042,
189
- "learning_rate": 1.9737329570996098e-05,
190
- "loss": 1.2454,
191
  "step": 260
192
  },
193
  {
194
- "epoch": 4.288,
195
- "grad_norm": 3.9374194145202637,
196
- "learning_rate": 1.968358744566884e-05,
197
- "loss": 1.2503,
198
  "step": 270
199
  },
200
  {
201
- "epoch": 4.448,
202
- "grad_norm": 4.536250591278076,
203
- "learning_rate": 1.9624934328034673e-05,
204
- "loss": 1.2983,
205
  "step": 280
206
  },
207
  {
208
- "epoch": 4.608,
209
- "grad_norm": 4.311966419219971,
210
- "learning_rate": 1.9561399963785586e-05,
211
- "loss": 1.2944,
212
  "step": 290
213
  },
214
  {
215
- "epoch": 4.768,
216
- "grad_norm": 4.188143253326416,
217
- "learning_rate": 1.9493016574118103e-05,
218
- "loss": 1.2997,
219
  "step": 300
220
  },
221
  {
222
- "epoch": 4.928,
223
- "grad_norm": 5.04379415512085,
224
- "learning_rate": 1.9419818839392408e-05,
225
- "loss": 1.2976,
226
  "step": 310
227
  },
228
  {
229
- "epoch": 5.08,
230
- "grad_norm": 4.528952598571777,
231
- "learning_rate": 1.9341843881544372e-05,
232
- "loss": 1.1579,
233
  "step": 320
234
  },
235
  {
236
- "epoch": 5.24,
237
- "grad_norm": 4.810428142547607,
238
- "learning_rate": 1.9259131245259293e-05,
239
- "loss": 1.13,
240
  "step": 330
241
  },
242
  {
243
- "epoch": 5.4,
244
- "grad_norm": 3.7566370964050293,
245
- "learning_rate": 1.917172287791698e-05,
246
- "loss": 1.1387,
247
  "step": 340
248
  },
249
  {
250
- "epoch": 5.5600000000000005,
251
- "grad_norm": 3.8142237663269043,
252
- "learning_rate": 1.9079663108318304e-05,
253
- "loss": 1.1176,
254
  "step": 350
255
  },
256
  {
257
- "epoch": 5.72,
258
- "grad_norm": 4.0017619132995605,
259
- "learning_rate": 1.8982998624204016e-05,
260
- "loss": 1.1042,
261
  "step": 360
262
  },
263
  {
264
- "epoch": 5.88,
265
- "grad_norm": 3.9953103065490723,
266
- "learning_rate": 1.8881778448577274e-05,
267
- "loss": 1.1386,
268
  "step": 370
269
  },
270
  {
271
- "epoch": 6.032,
272
- "grad_norm": 3.269265651702881,
273
- "learning_rate": 1.877605391484179e-05,
274
- "loss": 0.9651,
275
  "step": 380
276
  },
277
  {
278
- "epoch": 6.192,
279
- "grad_norm": 5.4509172439575195,
280
- "learning_rate": 1.8665878640768332e-05,
281
- "loss": 0.9487,
282
  "step": 390
283
  },
284
  {
285
- "epoch": 6.352,
286
- "grad_norm": 3.8790087699890137,
287
- "learning_rate": 1.855130850130267e-05,
288
- "loss": 0.9193,
289
  "step": 400
290
  },
291
  {
292
- "epoch": 6.5120000000000005,
293
- "grad_norm": 5.1756110191345215,
294
- "learning_rate": 1.8432401600228823e-05,
295
- "loss": 0.9112,
296
  "step": 410
297
  },
298
  {
299
- "epoch": 6.672,
300
- "grad_norm": 4.771461009979248,
301
- "learning_rate": 1.8309218240701973e-05,
302
- "loss": 0.9371,
303
  "step": 420
304
  },
305
  {
306
- "epoch": 6.832,
307
- "grad_norm": 4.88088846206665,
308
- "learning_rate": 1.818182089466595e-05,
309
- "loss": 1.0264,
310
  "step": 430
311
  },
312
  {
313
- "epoch": 6.992,
314
- "grad_norm": 4.158401012420654,
315
- "learning_rate": 1.8050274171170835e-05,
316
- "loss": 0.9534,
317
  "step": 440
318
  },
319
  {
320
- "epoch": 7.144,
321
- "grad_norm": 5.25468635559082,
322
- "learning_rate": 1.791464478360676e-05,
323
- "loss": 0.7345,
324
  "step": 450
325
  },
326
  {
327
- "epoch": 7.304,
328
- "grad_norm": 4.713033676147461,
329
- "learning_rate": 1.7775001515870466e-05,
330
- "loss": 0.8399,
331
  "step": 460
332
  },
333
  {
334
- "epoch": 7.464,
335
- "grad_norm": 5.714450359344482,
336
- "learning_rate": 1.7631415187481818e-05,
337
- "loss": 0.7525,
338
- "step": 470
339
- },
340
- {
341
- "epoch": 7.624,
342
- "grad_norm": 6.085780143737793,
343
- "learning_rate": 1.7483958617668e-05,
344
- "loss": 0.7276,
345
- "step": 480
346
- },
347
- {
348
- "epoch": 7.784,
349
- "grad_norm": 4.569671630859375,
350
- "learning_rate": 1.733270658843351e-05,
351
- "loss": 0.8071,
352
- "step": 490
353
- },
354
- {
355
- "epoch": 7.944,
356
- "grad_norm": 6.115426540374756,
357
- "learning_rate": 1.717773580663479e-05,
358
- "loss": 0.7683,
359
- "step": 500
360
- },
361
- {
362
- "epoch": 8.096,
363
- "grad_norm": 4.305016040802002,
364
- "learning_rate": 1.7019124865078625e-05,
365
- "loss": 0.6376,
366
- "step": 510
367
- },
368
- {
369
- "epoch": 8.256,
370
- "grad_norm": 6.470266342163086,
371
- "learning_rate": 1.6856954202664158e-05,
372
- "loss": 0.6286,
373
- "step": 520
374
- },
375
- {
376
- "epoch": 8.416,
377
- "grad_norm": 6.055320739746094,
378
- "learning_rate": 1.6691306063588583e-05,
379
- "loss": 0.6196,
380
- "step": 530
381
- },
382
- {
383
- "epoch": 8.576,
384
- "grad_norm": 6.73253870010376,
385
- "learning_rate": 1.652226445563737e-05,
386
- "loss": 0.564,
387
- "step": 540
388
- },
389
- {
390
- "epoch": 8.736,
391
- "grad_norm": 5.043179512023926,
392
- "learning_rate": 1.634991510758003e-05,
393
- "loss": 0.6122,
394
- "step": 550
395
- },
396
- {
397
- "epoch": 8.896,
398
- "grad_norm": 6.78087854385376,
399
- "learning_rate": 1.617434542569313e-05,
400
- "loss": 0.6173,
401
- "step": 560
402
- },
403
- {
404
- "epoch": 9.048,
405
- "grad_norm": 6.2355146408081055,
406
- "learning_rate": 1.5995644449432538e-05,
407
- "loss": 0.5342,
408
- "step": 570
409
- },
410
- {
411
- "epoch": 9.208,
412
- "grad_norm": 5.987257480621338,
413
- "learning_rate": 1.5813902806277445e-05,
414
- "loss": 0.4269,
415
- "step": 580
416
- },
417
- {
418
- "epoch": 9.368,
419
- "grad_norm": 5.455114364624023,
420
- "learning_rate": 1.562921266576898e-05,
421
- "loss": 0.4548,
422
- "step": 590
423
- },
424
- {
425
- "epoch": 9.528,
426
- "grad_norm": 5.296268463134766,
427
- "learning_rate": 1.5441667692766805e-05,
428
- "loss": 0.4038,
429
- "step": 600
430
- },
431
- {
432
- "epoch": 9.688,
433
- "grad_norm": 5.551358699798584,
434
- "learning_rate": 1.5251362999947386e-05,
435
- "loss": 0.4015,
436
- "step": 610
437
- },
438
- {
439
- "epoch": 9.848,
440
- "grad_norm": 4.464796543121338,
441
- "learning_rate": 1.5058395099567935e-05,
442
- "loss": 0.4353,
443
- "step": 620
444
- },
445
- {
446
- "epoch": 10.0,
447
- "grad_norm": 3.268158197402954,
448
- "learning_rate": 1.4862861854520652e-05,
449
- "loss": 0.3927,
450
- "step": 630
451
- },
452
- {
453
- "epoch": 10.16,
454
- "grad_norm": 8.046059608459473,
455
- "learning_rate": 1.4664862428701925e-05,
456
- "loss": 0.2612,
457
- "step": 640
458
- },
459
- {
460
- "epoch": 10.32,
461
- "grad_norm": 4.157690048217773,
462
- "learning_rate": 1.4464497236721779e-05,
463
- "loss": 0.2621,
464
- "step": 650
465
- },
466
- {
467
- "epoch": 10.48,
468
- "grad_norm": 5.3797688484191895,
469
- "learning_rate": 1.4261867892979e-05,
470
- "loss": 0.263,
471
- "step": 660
472
- },
473
- {
474
- "epoch": 10.64,
475
- "grad_norm": 4.068567276000977,
476
- "learning_rate": 1.4057077160127806e-05,
477
- "loss": 0.2492,
478
- "step": 670
479
- },
480
- {
481
- "epoch": 10.8,
482
- "grad_norm": 5.405711650848389,
483
- "learning_rate": 1.3850228896962178e-05,
484
- "loss": 0.2523,
485
- "step": 680
486
- },
487
- {
488
- "epoch": 10.96,
489
- "grad_norm": 4.762354373931885,
490
- "learning_rate": 1.3641428005744308e-05,
491
- "loss": 0.2586,
492
- "step": 690
493
- },
494
- {
495
- "epoch": 11.112,
496
- "grad_norm": 5.127146244049072,
497
- "learning_rate": 1.3430780379003814e-05,
498
- "loss": 0.1699,
499
- "step": 700
500
- },
501
- {
502
- "epoch": 11.272,
503
- "grad_norm": 3.0993189811706543,
504
- "learning_rate": 1.3218392845834789e-05,
505
- "loss": 0.1514,
506
- "step": 710
507
- },
508
- {
509
- "epoch": 11.432,
510
- "grad_norm": 5.754135608673096,
511
- "learning_rate": 1.300437311771785e-05,
512
- "loss": 0.1432,
513
- "step": 720
514
- },
515
- {
516
- "epoch": 11.592,
517
- "grad_norm": 4.12827730178833,
518
- "learning_rate": 1.2788829733894698e-05,
519
- "loss": 0.1512,
520
- "step": 730
521
- },
522
- {
523
- "epoch": 11.752,
524
- "grad_norm": 4.6962175369262695,
525
- "learning_rate": 1.257187200632289e-05,
526
- "loss": 0.1534,
527
- "step": 740
528
- },
529
- {
530
- "epoch": 11.912,
531
- "grad_norm": 6.317523002624512,
532
- "learning_rate": 1.2353609964238686e-05,
533
- "loss": 0.1452,
534
- "step": 750
535
- },
536
- {
537
- "epoch": 12.064,
538
- "grad_norm": 2.793424367904663,
539
- "learning_rate": 1.213415429835621e-05,
540
- "loss": 0.1167,
541
- "step": 760
542
- },
543
- {
544
- "epoch": 12.224,
545
- "grad_norm": 3.816258668899536,
546
- "learning_rate": 1.1913616304731064e-05,
547
- "loss": 0.0785,
548
- "step": 770
549
- },
550
- {
551
- "epoch": 12.384,
552
- "grad_norm": 3.989567518234253,
553
- "learning_rate": 1.1692107828317014e-05,
554
- "loss": 0.0857,
555
- "step": 780
556
- },
557
- {
558
- "epoch": 12.544,
559
- "grad_norm": 4.456111431121826,
560
- "learning_rate": 1.1469741206244249e-05,
561
- "loss": 0.0862,
562
- "step": 790
563
- },
564
- {
565
- "epoch": 12.704,
566
- "grad_norm": 4.539771556854248,
567
- "learning_rate": 1.1246629210848062e-05,
568
- "loss": 0.0949,
569
- "step": 800
570
- },
571
- {
572
- "epoch": 12.864,
573
- "grad_norm": 2.4530129432678223,
574
- "learning_rate": 1.1022884992476826e-05,
575
- "loss": 0.0928,
576
- "step": 810
577
- },
578
- {
579
- "epoch": 13.016,
580
- "grad_norm": 2.042999267578125,
581
- "learning_rate": 1.0821068423364156e-05,
582
- "loss": 0.0951,
583
- "step": 820
584
- },
585
- {
586
- "epoch": 13.176,
587
- "grad_norm": 2.9049434661865234,
588
- "learning_rate": 1.0596435812513276e-05,
589
- "loss": 0.0483,
590
- "step": 830
591
- },
592
- {
593
- "epoch": 13.336,
594
- "grad_norm": 2.3502166271209717,
595
- "learning_rate": 1.037150072164626e-05,
596
- "loss": 0.0559,
597
- "step": 840
598
- },
599
- {
600
- "epoch": 13.496,
601
- "grad_norm": 2.2428765296936035,
602
- "learning_rate": 1.0146377225686996e-05,
603
- "loss": 0.0801,
604
- "step": 850
605
- },
606
- {
607
- "epoch": 13.656,
608
- "grad_norm": 5.673745155334473,
609
- "learning_rate": 9.921179495108249e-06,
610
- "loss": 0.0683,
611
- "step": 860
612
- },
613
- {
614
- "epoch": 13.816,
615
- "grad_norm": 3.9386937618255615,
616
- "learning_rate": 9.696021738030575e-06,
617
- "loss": 0.0616,
618
- "step": 870
619
- },
620
- {
621
- "epoch": 13.975999999999999,
622
- "grad_norm": 4.362432479858398,
623
- "learning_rate": 9.471018142302127e-06,
624
- "loss": 0.058,
625
- "step": 880
626
- },
627
- {
628
- "epoch": 14.128,
629
- "grad_norm": 2.225241184234619,
630
- "learning_rate": 9.24628281758876e-06,
631
- "loss": 0.0356,
632
- "step": 890
633
- },
634
- {
635
- "epoch": 14.288,
636
- "grad_norm": 4.0786356925964355,
637
- "learning_rate": 9.021929737503757e-06,
638
- "loss": 0.0458,
639
- "step": 900
640
- },
641
- {
642
- "epoch": 14.448,
643
- "grad_norm": 2.464179277420044,
644
- "learning_rate": 8.79807268180658e-06,
645
- "loss": 0.0531,
646
- "step": 910
647
- },
648
- {
649
- "epoch": 14.608,
650
- "grad_norm": 2.679661273956299,
651
- "learning_rate": 8.574825178699935e-06,
652
- "loss": 0.0359,
653
- "step": 920
654
- },
655
- {
656
- "epoch": 14.768,
657
- "grad_norm": 2.0911498069763184,
658
- "learning_rate": 8.352300447254372e-06,
659
- "loss": 0.0362,
660
- "step": 930
661
- },
662
- {
663
- "epoch": 14.928,
664
- "grad_norm": 2.3030571937561035,
665
- "learning_rate": 8.130611339989731e-06,
666
- "loss": 0.0292,
667
- "step": 940
668
- },
669
- {
670
- "epoch": 15.08,
671
- "grad_norm": 1.6733816862106323,
672
- "learning_rate": 7.909870285642403e-06,
673
- "loss": 0.0241,
674
- "step": 950
675
- },
676
- {
677
- "epoch": 15.24,
678
- "grad_norm": 1.4519929885864258,
679
- "learning_rate": 7.690189232147566e-06,
680
- "loss": 0.0264,
681
- "step": 960
682
- },
683
- {
684
- "epoch": 15.4,
685
- "grad_norm": 1.980666995048523,
686
- "learning_rate": 7.4716795898652615e-06,
687
- "loss": 0.0231,
688
- "step": 970
689
- },
690
- {
691
- "epoch": 15.56,
692
- "grad_norm": 2.6794183254241943,
693
- "learning_rate": 7.2544521750790345e-06,
694
- "loss": 0.0243,
695
- "step": 980
696
- },
697
- {
698
- "epoch": 15.72,
699
- "grad_norm": 1.8193122148513794,
700
- "learning_rate": 7.038617153795948e-06,
701
- "loss": 0.0226,
702
- "step": 990
703
- },
704
- {
705
- "epoch": 15.88,
706
- "grad_norm": 2.1489455699920654,
707
- "learning_rate": 6.82428398587631e-06,
708
- "loss": 0.0321,
709
- "step": 1000
710
- },
711
- {
712
- "epoch": 16.032,
713
- "grad_norm": 0.9566267728805542,
714
- "learning_rate": 6.611561369521546e-06,
715
- "loss": 0.019,
716
- "step": 1010
717
- },
718
- {
719
- "epoch": 16.192,
720
- "grad_norm": 0.45050784945487976,
721
- "learning_rate": 6.400557186148371e-06,
722
- "loss": 0.0101,
723
- "step": 1020
724
- },
725
- {
726
- "epoch": 16.352,
727
- "grad_norm": 3.0079352855682373,
728
- "learning_rate": 6.191378445677125e-06,
729
- "loss": 0.0139,
730
- "step": 1030
731
- },
732
- {
733
- "epoch": 16.512,
734
- "grad_norm": 1.0027068853378296,
735
- "learning_rate": 5.984131232262167e-06,
736
- "loss": 0.0264,
737
- "step": 1040
738
- },
739
- {
740
- "epoch": 16.672,
741
- "grad_norm": 0.34918779134750366,
742
- "learning_rate": 5.7789206504916815e-06,
743
- "loss": 0.0123,
744
- "step": 1050
745
- },
746
- {
747
- "epoch": 16.832,
748
- "grad_norm": 1.0329653024673462,
749
- "learning_rate": 5.5758507720843425e-06,
750
- "loss": 0.0115,
751
- "step": 1060
752
- },
753
- {
754
- "epoch": 16.992,
755
- "grad_norm": 1.9161659479141235,
756
- "learning_rate": 5.375024583109745e-06,
757
- "loss": 0.0135,
758
- "step": 1070
759
- },
760
- {
761
- "epoch": 17.144,
762
- "grad_norm": 0.42554718255996704,
763
- "learning_rate": 5.176543931759447e-06,
764
- "loss": 0.005,
765
- "step": 1080
766
- },
767
- {
768
- "epoch": 17.304,
769
- "grad_norm": 0.7298970818519592,
770
- "learning_rate": 4.980509476695043e-06,
771
- "loss": 0.0096,
772
- "step": 1090
773
- },
774
- {
775
- "epoch": 17.464,
776
- "grad_norm": 2.393183946609497,
777
- "learning_rate": 4.7870206359995815e-06,
778
- "loss": 0.0148,
779
- "step": 1100
780
- },
781
- {
782
- "epoch": 17.624,
783
- "grad_norm": 0.4778424799442291,
784
- "learning_rate": 4.596175536758024e-06,
785
- "loss": 0.0067,
786
- "step": 1110
787
- },
788
- {
789
- "epoch": 17.784,
790
- "grad_norm": 0.22980810701847076,
791
- "learning_rate": 4.408070965292534e-06,
792
- "loss": 0.0053,
793
- "step": 1120
794
- },
795
- {
796
- "epoch": 17.944,
797
- "grad_norm": 0.18192055821418762,
798
- "learning_rate": 4.222802318077664e-06,
799
- "loss": 0.0079,
800
- "step": 1130
801
- },
802
- {
803
- "epoch": 18.096,
804
- "grad_norm": 0.6733874678611755,
805
- "learning_rate": 4.040463553360431e-06,
806
- "loss": 0.0039,
807
- "step": 1140
808
- },
809
- {
810
- "epoch": 18.256,
811
- "grad_norm": 0.17421452701091766,
812
- "learning_rate": 3.861147143509754e-06,
813
- "loss": 0.0023,
814
- "step": 1150
815
- },
816
- {
817
- "epoch": 18.416,
818
- "grad_norm": 0.15809208154678345,
819
- "learning_rate": 3.6849440281194813e-06,
820
- "loss": 0.006,
821
- "step": 1160
822
- },
823
- {
824
- "epoch": 18.576,
825
- "grad_norm": 0.06922920793294907,
826
- "learning_rate": 3.5119435678887328e-06,
827
- "loss": 0.0023,
828
- "step": 1170
829
- },
830
- {
831
- "epoch": 18.736,
832
- "grad_norm": 0.08193696290254593,
833
- "learning_rate": 3.342233499302985e-06,
834
- "loss": 0.003,
835
- "step": 1180
836
- },
837
- {
838
- "epoch": 18.896,
839
- "grad_norm": 0.0757126435637474,
840
- "learning_rate": 3.175899890138858e-06,
841
- "loss": 0.002,
842
- "step": 1190
843
- },
844
- {
845
- "epoch": 19.048,
846
- "grad_norm": 0.057399798184633255,
847
- "learning_rate": 3.0130270958152196e-06,
848
- "loss": 0.0022,
849
- "step": 1200
850
- },
851
- {
852
- "epoch": 19.208,
853
- "grad_norm": 0.068113774061203,
854
- "learning_rate": 2.8536977166126234e-06,
855
- "loss": 0.0022,
856
- "step": 1210
857
- },
858
- {
859
- "epoch": 19.368,
860
- "grad_norm": 0.06517008692026138,
861
- "learning_rate": 2.697992555782969e-06,
862
- "loss": 0.0016,
863
- "step": 1220
864
- },
865
- {
866
- "epoch": 19.528,
867
- "grad_norm": 0.07533544301986694,
868
- "learning_rate": 2.545990578570404e-06,
869
- "loss": 0.0015,
870
- "step": 1230
871
- },
872
- {
873
- "epoch": 19.688,
874
- "grad_norm": 0.08159100264310837,
875
- "learning_rate": 2.397768872164462e-06,
876
- "loss": 0.0018,
877
- "step": 1240
878
- },
879
- {
880
- "epoch": 19.848,
881
- "grad_norm": 0.05212102085351944,
882
- "learning_rate": 2.253402606605577e-06,
883
- "loss": 0.0014,
884
- "step": 1250
885
- },
886
- {
887
- "epoch": 20.0,
888
- "grad_norm": 0.038643430918455124,
889
- "learning_rate": 2.1129649966629185e-06,
890
- "loss": 0.0013,
891
- "step": 1260
892
- },
893
- {
894
- "epoch": 20.16,
895
- "grad_norm": 0.040117453783750534,
896
- "learning_rate": 1.9765272647038038e-06,
897
- "loss": 0.0013,
898
- "step": 1270
899
- },
900
- {
901
- "epoch": 20.32,
902
- "grad_norm": 0.03363404422998428,
903
- "learning_rate": 1.8441586045735737e-06,
904
- "loss": 0.0011,
905
- "step": 1280
906
- },
907
- {
908
- "epoch": 20.48,
909
- "grad_norm": 0.055696483701467514,
910
- "learning_rate": 1.7159261465041954e-06,
911
- "loss": 0.0013,
912
- "step": 1290
913
- },
914
- {
915
- "epoch": 20.64,
916
- "grad_norm": 0.0553043931722641,
917
- "learning_rate": 1.5918949230694635e-06,
918
- "loss": 0.0014,
919
- "step": 1300
920
- },
921
- {
922
- "epoch": 20.8,
923
- "grad_norm": 0.049317434430122375,
924
- "learning_rate": 1.4721278362039626e-06,
925
- "loss": 0.0011,
926
- "step": 1310
927
- },
928
- {
929
- "epoch": 20.96,
930
- "grad_norm": 0.07064161449670792,
931
- "learning_rate": 1.356685625302625e-06,
932
- "loss": 0.0012,
933
- "step": 1320
934
- },
935
- {
936
- "epoch": 21.112,
937
- "grad_norm": 0.0384482778608799,
938
- "learning_rate": 1.2456268364169853e-06,
939
- "loss": 0.0011,
940
- "step": 1330
941
- },
942
- {
943
- "epoch": 21.272,
944
- "grad_norm": 0.04504753276705742,
945
- "learning_rate": 1.1390077925637865e-06,
946
- "loss": 0.0011,
947
- "step": 1340
948
- },
949
- {
950
- "epoch": 21.432,
951
- "grad_norm": 0.04046454280614853,
952
- "learning_rate": 1.0368825651609893e-06,
953
- "loss": 0.001,
954
- "step": 1350
955
- },
956
- {
957
- "epoch": 21.592,
958
- "grad_norm": 0.04408493638038635,
959
- "learning_rate": 9.393029466056714e-07,
960
- "loss": 0.0012,
961
- "step": 1360
962
- },
963
- {
964
- "epoch": 21.752,
965
- "grad_norm": 0.03646273910999298,
966
- "learning_rate": 8.463184240077172e-07,
967
- "loss": 0.0012,
968
- "step": 1370
969
- },
970
- {
971
- "epoch": 21.912,
972
- "grad_norm": 0.03203440457582474,
973
- "learning_rate": 7.579761540926434e-07,
974
- "loss": 0.0011,
975
- "step": 1380
976
- },
977
- {
978
- "epoch": 22.064,
979
- "grad_norm": 0.03588934242725372,
980
- "learning_rate": 6.743209392862349e-07,
981
- "loss": 0.001,
982
- "step": 1390
983
- },
984
- {
985
- "epoch": 22.224,
986
- "grad_norm": 0.0342290997505188,
987
- "learning_rate": 5.953952049931999e-07,
988
- "loss": 0.0011,
989
- "step": 1400
990
- },
991
- {
992
- "epoch": 22.384,
993
- "grad_norm": 0.036632440984249115,
994
- "learning_rate": 5.212389780812733e-07,
995
- "loss": 0.001,
996
- "step": 1410
997
- },
998
- {
999
- "epoch": 22.544,
1000
- "grad_norm": 0.03759520500898361,
1001
- "learning_rate": 4.518898665817695e-07,
1002
- "loss": 0.0011,
1003
- "step": 1420
1004
- },
1005
- {
1006
- "epoch": 22.704,
1007
- "grad_norm": 0.03835231438279152,
1008
- "learning_rate": 3.8738304061681107e-07,
1009
- "loss": 0.0011,
1010
- "step": 1430
1011
- },
1012
- {
1013
- "epoch": 22.864,
1014
- "grad_norm": 0.042444001883268356,
1015
- "learning_rate": 3.2775121456295024e-07,
1016
- "loss": 0.0011,
1017
- "step": 1440
1018
- },
1019
- {
1020
- "epoch": 23.016,
1021
- "grad_norm": 0.033434733748435974,
1022
- "learning_rate": 2.730246304601991e-07,
1023
- "loss": 0.001,
1024
- "step": 1450
1025
- },
1026
- {
1027
- "epoch": 23.176,
1028
- "grad_norm": 0.03470597416162491,
1029
- "learning_rate": 2.2323104267490404e-07,
1030
- "loss": 0.0011,
1031
- "step": 1460
1032
- },
1033
- {
1034
- "epoch": 23.336,
1035
- "grad_norm": 0.04532945156097412,
1036
- "learning_rate": 1.783957038242279e-07,
1037
- "loss": 0.001,
1038
- "step": 1470
1039
- },
1040
- {
1041
- "epoch": 23.496,
1042
- "grad_norm": 0.035716019570827484,
1043
- "learning_rate": 1.3854135196939345e-07,
1044
- "loss": 0.001,
1045
- "step": 1480
1046
- },
1047
- {
1048
- "epoch": 23.656,
1049
- "grad_norm": 0.03435162454843521,
1050
- "learning_rate": 1.0368819908415983e-07,
1051
- "loss": 0.0011,
1052
- "step": 1490
1053
- },
1054
- {
1055
- "epoch": 23.816,
1056
- "grad_norm": 0.04788799211382866,
1057
- "learning_rate": 7.385392080440535e-08,
1058
- "loss": 0.0011,
1059
- "step": 1500
1060
- },
1061
- {
1062
- "epoch": 23.976,
1063
- "grad_norm": 0.037617627531290054,
1064
- "learning_rate": 4.905364746400021e-08,
1065
- "loss": 0.0011,
1066
- "step": 1510
1067
- },
1068
- {
1069
- "epoch": 24.128,
1070
- "grad_norm": 0.04006591811776161,
1071
- "learning_rate": 2.929995642151906e-08,
1072
- "loss": 0.001,
1073
- "step": 1520
1074
- },
1075
- {
1076
- "epoch": 24.288,
1077
- "grad_norm": 0.03150051832199097,
1078
- "learning_rate": 1.4602865681682122e-08,
1079
- "loss": 0.001,
1080
- "step": 1530
1081
- },
1082
- {
1083
- "epoch": 24.448,
1084
- "grad_norm": 0.04720960184931755,
1085
- "learning_rate": 4.969828814767042e-09,
1086
- "loss": 0.001,
1087
- "step": 1540
1088
- },
1089
- {
1090
- "epoch": 24.608,
1091
- "grad_norm": 0.0407867431640625,
1092
- "learning_rate": 4.0573117655595684e-10,
1093
- "loss": 0.001,
1094
- "step": 1550
1095
- },
1096
- {
1097
- "epoch": 24.608,
1098
- "step": 1550,
1099
- "total_flos": 1.324081921088553e+17,
1100
- "train_loss": 0.672794044127147,
1101
- "train_runtime": 33908.1665,
1102
- "train_samples_per_second": 0.369,
1103
- "train_steps_per_second": 0.046
1104
  }
1105
  ],
1106
  "logging_steps": 10,
1107
- "max_steps": 1550,
1108
  "num_input_tokens_seen": 0,
1109
- "num_train_epochs": 25,
1110
  "save_steps": 1000,
1111
  "stateful_callbacks": {
1112
  "TrainerControl": {
@@ -1120,8 +357,8 @@
1120
  "attributes": {}
1121
  }
1122
  },
1123
- "total_flos": 1.324081921088553e+17,
1124
- "train_batch_size": 2,
1125
  "trial_name": null,
1126
  "trial_params": null
1127
  }
 
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
+ "epoch": 14.544,
5
  "eval_steps": 500,
6
+ "global_step": 465,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
+ "epoch": 0.32,
13
+ "grad_norm": 72.67546081542969,
14
+ "learning_rate": 3.8297872340425535e-06,
15
+ "loss": 10.0348,
16
  "step": 10
17
  },
18
  {
19
+ "epoch": 0.64,
20
+ "grad_norm": 41.243839263916016,
21
+ "learning_rate": 8.085106382978723e-06,
22
+ "loss": 4.7312,
23
  "step": 20
24
  },
25
  {
26
+ "epoch": 0.96,
27
+ "grad_norm": 34.776241302490234,
28
+ "learning_rate": 1.2340425531914895e-05,
29
+ "loss": 3.4362,
30
  "step": 30
31
  },
32
  {
33
+ "epoch": 1.256,
34
+ "grad_norm": 12.210166931152344,
35
+ "learning_rate": 1.6595744680851064e-05,
36
+ "loss": 2.5739,
37
  "step": 40
38
  },
39
  {
40
+ "epoch": 1.576,
41
+ "grad_norm": 11.936144828796387,
42
+ "learning_rate": 1.9998870284726968e-05,
43
+ "loss": 2.4828,
44
  "step": 50
45
  },
46
  {
47
+ "epoch": 1.896,
48
+ "grad_norm": 5.305131912231445,
49
+ "learning_rate": 1.9959357045100764e-05,
50
+ "loss": 2.1904,
51
  "step": 60
52
  },
53
  {
54
+ "epoch": 2.192,
55
+ "grad_norm": 6.481784820556641,
56
+ "learning_rate": 1.9863613034027224e-05,
57
+ "loss": 1.893,
58
  "step": 70
59
  },
60
  {
61
+ "epoch": 2.512,
62
+ "grad_norm": 2.9933059215545654,
63
+ "learning_rate": 1.971217882451521e-05,
64
+ "loss": 1.9328,
65
  "step": 80
66
  },
67
  {
68
+ "epoch": 2.832,
69
+ "grad_norm": 5.0720906257629395,
70
+ "learning_rate": 1.9505909417784758e-05,
71
+ "loss": 1.8361,
72
  "step": 90
73
  },
74
  {
75
+ "epoch": 3.128,
76
+ "grad_norm": 4.453537940979004,
77
+ "learning_rate": 1.9245969415909464e-05,
78
+ "loss": 1.6677,
79
  "step": 100
80
  },
81
  {
82
+ "epoch": 3.448,
83
+ "grad_norm": 3.9254183769226074,
84
+ "learning_rate": 1.8933826446444933e-05,
85
+ "loss": 1.7492,
86
  "step": 110
87
  },
88
  {
89
+ "epoch": 3.768,
90
+ "grad_norm": 2.421752691268921,
91
+ "learning_rate": 1.8571242876167995e-05,
92
+ "loss": 1.6435,
93
  "step": 120
94
  },
95
  {
96
+ "epoch": 4.064,
97
+ "grad_norm": 3.5012094974517822,
98
+ "learning_rate": 1.8160265860711134e-05,
99
+ "loss": 1.478,
100
  "step": 130
101
  },
102
  {
103
+ "epoch": 4.384,
104
+ "grad_norm": 4.192974090576172,
105
+ "learning_rate": 1.770321578627213e-05,
106
+ "loss": 1.4807,
107
  "step": 140
108
  },
109
  {
110
+ "epoch": 4.704,
111
+ "grad_norm": 2.528031826019287,
112
+ "learning_rate": 1.7202673168657318e-05,
113
+ "loss": 1.375,
114
  "step": 150
115
  },
116
  {
117
+ "epoch": 5.0,
118
+ "grad_norm": 1.0680221319198608,
119
+ "learning_rate": 1.6661464083626734e-05,
120
+ "loss": 1.2751,
121
  "step": 160
122
  },
123
  {
124
+ "epoch": 5.32,
125
+ "grad_norm": 2.499868392944336,
126
+ "learning_rate": 1.6082644210801846e-05,
127
+ "loss": 1.2887,
128
  "step": 170
129
  },
130
  {
131
+ "epoch": 5.64,
132
+ "grad_norm": 2.785773754119873,
133
+ "learning_rate": 1.5469481581224274e-05,
134
+ "loss": 1.2852,
135
  "step": 180
136
  },
137
  {
138
+ "epoch": 5.96,
139
+ "grad_norm": 2.820884943008423,
140
+ "learning_rate": 1.4825438125973263e-05,
141
+ "loss": 1.2329,
142
  "step": 190
143
  },
144
  {
145
+ "epoch": 6.256,
146
+ "grad_norm": 2.5425021648406982,
147
+ "learning_rate": 1.4154150130018867e-05,
148
+ "loss": 1.1001,
149
  "step": 200
150
  },
151
  {
152
+ "epoch": 6.576,
153
+ "grad_norm": 2.7974514961242676,
154
+ "learning_rate": 1.3459407701668762e-05,
155
+ "loss": 1.1543,
156
  "step": 210
157
  },
158
  {
159
+ "epoch": 6.896,
160
+ "grad_norm": 2.438002586364746,
161
+ "learning_rate": 1.2745133373524855e-05,
162
+ "loss": 1.132,
163
  "step": 220
164
  },
165
  {
166
+ "epoch": 7.192,
167
+ "grad_norm": 2.9781107902526855,
168
+ "learning_rate": 1.2015359955769021e-05,
169
+ "loss": 1.0284,
170
  "step": 230
171
  },
172
  {
173
+ "epoch": 7.5120000000000005,
174
+ "grad_norm": 3.271495819091797,
175
+ "learning_rate": 1.127420776681905e-05,
176
+ "loss": 1.0392,
177
  "step": 240
178
  },
179
  {
180
+ "epoch": 7.832,
181
+ "grad_norm": 3.1173477172851562,
182
+ "learning_rate": 1.0525861369910877e-05,
183
+ "loss": 1.0436,
184
  "step": 250
185
  },
186
  {
187
+ "epoch": 8.128,
188
+ "grad_norm": 2.84490704536438,
189
+ "learning_rate": 9.77454594695308e-06,
190
+ "loss": 0.8973,
191
  "step": 260
192
  },
193
  {
194
+ "epoch": 8.448,
195
+ "grad_norm": 3.3770253658294678,
196
+ "learning_rate": 9.024503443047318e-06,
197
+ "loss": 0.9455,
198
  "step": 270
199
  },
200
  {
201
+ "epoch": 8.768,
202
+ "grad_norm": 3.168492317199707,
203
+ "learning_rate": 8.279968616363417e-06,
204
+ "loss": 0.9297,
205
  "step": 280
206
  },
207
  {
208
+ "epoch": 9.064,
209
+ "grad_norm": 3.5850722789764404,
210
+ "learning_rate": 7.545145128592009e-06,
211
+ "loss": 0.8414,
212
  "step": 290
213
  },
214
  {
215
+ "epoch": 9.384,
216
+ "grad_norm": 2.5484402179718018,
217
+ "learning_rate": 6.824181810968675e-06,
218
+ "loss": 0.8513,
219
  "step": 300
220
  },
221
  {
222
+ "epoch": 9.704,
223
+ "grad_norm": 3.354924201965332,
224
+ "learning_rate": 6.121149239872151e-06,
225
+ "loss": 0.8351,
226
  "step": 310
227
  },
228
  {
229
+ "epoch": 10.0,
230
+ "grad_norm": 1.4634054899215698,
231
+ "learning_rate": 5.440016754251364e-06,
232
+ "loss": 0.7886,
233
  "step": 320
234
  },
235
  {
236
+ "epoch": 10.32,
237
+ "grad_norm": 3.3187077045440674,
238
+ "learning_rate": 4.784630044641435e-06,
239
+ "loss": 0.7832,
240
  "step": 330
241
  },
242
  {
243
+ "epoch": 10.64,
244
+ "grad_norm": 2.827324390411377,
245
+ "learning_rate": 4.1586894403016576e-06,
246
+ "loss": 0.7555,
247
  "step": 340
248
  },
249
  {
250
+ "epoch": 10.96,
251
+ "grad_norm": 2.74627685546875,
252
+ "learning_rate": 3.565729017066729e-06,
253
+ "loss": 0.7529,
254
  "step": 350
255
  },
256
  {
257
+ "epoch": 11.256,
258
+ "grad_norm": 2.8250672817230225,
259
+ "learning_rate": 3.0090966438688774e-06,
260
+ "loss": 0.6507,
261
  "step": 360
262
  },
263
  {
264
+ "epoch": 11.576,
265
+ "grad_norm": 3.070279359817505,
266
+ "learning_rate": 2.491935080588658e-06,
267
+ "loss": 0.7048,
268
  "step": 370
269
  },
270
  {
271
+ "epoch": 11.896,
272
+ "grad_norm": 2.929745674133301,
273
+ "learning_rate": 2.01716423395644e-06,
274
+ "loss": 0.6911,
275
  "step": 380
276
  },
277
  {
278
+ "epoch": 12.192,
279
+ "grad_norm": 2.552579879760742,
280
+ "learning_rate": 1.587464671688187e-06,
281
+ "loss": 0.6039,
282
  "step": 390
283
  },
284
  {
285
+ "epoch": 12.512,
286
+ "grad_norm": 2.608180046081543,
287
+ "learning_rate": 1.2052624879351105e-06,
288
+ "loss": 0.6456,
289
  "step": 400
290
  },
291
  {
292
+ "epoch": 12.832,
293
+ "grad_norm": 2.6534199714660645,
294
+ "learning_rate": 8.727156054972374e-07,
295
+ "loss": 0.6479,
296
  "step": 410
297
  },
298
  {
299
+ "epoch": 13.128,
300
+ "grad_norm": 2.4939088821411133,
301
+ "learning_rate": 5.917015921389569e-07,
302
+ "loss": 0.6013,
303
  "step": 420
304
  },
305
  {
306
+ "epoch": 13.448,
307
+ "grad_norm": 2.7369675636291504,
308
+ "learning_rate": 3.638070597958665e-07,
309
+ "loss": 0.6168,
310
  "step": 430
311
  },
312
  {
313
+ "epoch": 13.768,
314
+ "grad_norm": 2.4181711673736572,
315
+ "learning_rate": 1.903187065253076e-07,
316
+ "loss": 0.6093,
317
  "step": 440
318
  },
319
  {
320
+ "epoch": 14.064,
321
+ "grad_norm": 2.7222864627838135,
322
+ "learning_rate": 7.22160517779169e-08,
323
+ "loss": 0.5911,
324
  "step": 450
325
  },
326
  {
327
+ "epoch": 14.384,
328
+ "grad_norm": 2.8161678314208984,
329
+ "learning_rate": 1.0165906007056914e-08,
330
+ "loss": 0.6135,
331
  "step": 460
332
  },
333
  {
334
+ "epoch": 14.544,
335
+ "step": 465,
336
+ "total_flos": 1.565274744469586e+17,
337
+ "train_loss": 1.4569768874875961,
338
+ "train_runtime": 22995.3507,
339
+ "train_samples_per_second": 0.652,
340
+ "train_steps_per_second": 0.02
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
341
  }
342
  ],
343
  "logging_steps": 10,
344
+ "max_steps": 465,
345
  "num_input_tokens_seen": 0,
346
+ "num_train_epochs": 15,
347
  "save_steps": 1000,
348
  "stateful_callbacks": {
349
  "TrainerControl": {
 
357
  "attributes": {}
358
  }
359
  },
360
+ "total_flos": 1.565274744469586e+17,
361
+ "train_batch_size": 4,
362
  "trial_name": null,
363
  "trial_params": null
364
  }
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:dc45890bd2d24eb38ee6085d083cd1874d1991cf87176f31b08f0cafc9576e6c
3
  size 5688
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7965a2214104df656922b1be16c3a7c2b84d436985ed36667de02fc406d2a34b
3
  size 5688