wckwan commited on
Commit
0dc997d
·
verified ·
1 Parent(s): 108e05b

Model save

Browse files
README.md CHANGED
@@ -1,11 +1,9 @@
1
  ---
2
- base_model: Qwen/Qwen2.5-Math-7B
3
- datasets: DigitalLearningGmbH/MATH-lighteval
4
  library_name: transformers
5
  model_name: Qwen-2.5-7B-Simple-RL
6
  tags:
7
  - generated_from_trainer
8
- - open-r1
9
  - trl
10
  - grpo
11
  licence: license
@@ -13,7 +11,7 @@ licence: license
13
 
14
  # Model Card for Qwen-2.5-7B-Simple-RL
15
 
16
- This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
17
  It has been trained using [TRL](https://github.com/huggingface/trl).
18
 
19
  ## Quick start
@@ -29,7 +27,7 @@ print(output["generated_text"])
29
 
30
  ## Training procedure
31
 
32
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/cyruskwan/open-r1/runs/hjcgoqm1)
33
 
34
 
35
  This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
 
1
  ---
2
+ base_model: Qwen/Qwen2.5-Math-7B-Instruct
 
3
  library_name: transformers
4
  model_name: Qwen-2.5-7B-Simple-RL
5
  tags:
6
  - generated_from_trainer
 
7
  - trl
8
  - grpo
9
  licence: license
 
11
 
12
  # Model Card for Qwen-2.5-7B-Simple-RL
13
 
14
+ This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct).
15
  It has been trained using [TRL](https://github.com/huggingface/trl).
16
 
17
  ## Quick start
 
27
 
28
  ## Training procedure
29
 
30
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/cyruskwan/open-r1/runs/xoeuq0c9)
31
 
32
 
33
  This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
all_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
  "total_flos": 0.0,
3
- "train_loss": 0.028255671029910445,
4
- "train_runtime": 36935.2831,
5
  "train_samples": 7500,
6
- "train_samples_per_second": 0.203,
7
- "train_steps_per_second": 0.001
8
  }
 
1
  {
2
  "total_flos": 0.0,
3
+ "train_loss": 0.1694948914914559,
4
+ "train_runtime": 74169.3594,
5
  "train_samples": 7500,
6
+ "train_samples_per_second": 0.101,
7
+ "train_steps_per_second": 0.002
8
  }
config.json CHANGED
@@ -4,7 +4,7 @@
4
  ],
5
  "attention_dropout": 0.0,
6
  "bos_token_id": 151643,
7
- "eos_token_id": 151643,
8
  "hidden_act": "silu",
9
  "hidden_size": 3584,
10
  "initializer_range": 0.02,
@@ -17,13 +17,12 @@
17
  "num_key_value_heads": 4,
18
  "rms_norm_eps": 1e-06,
19
  "rope_scaling": null,
20
- "rope_theta": 10000,
21
  "sliding_window": 4096,
22
  "tie_word_embeddings": false,
23
  "torch_dtype": "bfloat16",
24
  "transformers_version": "4.50.0",
25
- "use_cache": true,
26
- "use_mrope": false,
27
  "use_sliding_window": false,
28
  "vocab_size": 152064
29
  }
 
4
  ],
5
  "attention_dropout": 0.0,
6
  "bos_token_id": 151643,
7
+ "eos_token_id": 151645,
8
  "hidden_act": "silu",
9
  "hidden_size": 3584,
10
  "initializer_range": 0.02,
 
17
  "num_key_value_heads": 4,
18
  "rms_norm_eps": 1e-06,
19
  "rope_scaling": null,
20
+ "rope_theta": 10000.0,
21
  "sliding_window": 4096,
22
  "tie_word_embeddings": false,
23
  "torch_dtype": "bfloat16",
24
  "transformers_version": "4.50.0",
25
+ "use_cache": false,
 
26
  "use_sliding_window": false,
27
  "vocab_size": 152064
28
  }
generation_config.json CHANGED
@@ -1,6 +1,9 @@
1
  {
2
  "bos_token_id": 151643,
3
- "eos_token_id": 151643,
4
- "max_new_tokens": 2048,
 
 
 
5
  "transformers_version": "4.50.0"
6
  }
 
1
  {
2
  "bos_token_id": 151643,
3
+ "eos_token_id": [
4
+ 151645,
5
+ 151643
6
+ ],
7
+ "pad_token_id": 151643,
8
  "transformers_version": "4.50.0"
9
  }
model-00001-of-00004.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:67a84a79ce3e4b09530b80cacf3bfb34e7e032df6e3b16a781b2bc07188e8b3f
3
  size 4877660776
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b8843653ab97f66ef52ec60f955e758344b765b8d832a1d64ad1b59643e341fd
3
  size 4877660776
model-00002-of-00004.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6a159a8a5dcc8f9d3ecaa17119169e5886eff14df9e5ce9b0f19c653749082af
3
  size 4932751008
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:479a1b36a162285708400e0fbebe6bd4a7d674cb6002d7442118bed9a2df00f4
3
  size 4932751008
model-00003-of-00004.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e53d996d4793e766dfbe9ffee667e58a1546bb7a52974160ff3f9720369ebfb3
3
  size 4330865200
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:21ac08b7265fe178a5909fbd0eac4ae746c85c17552d2b43018834dbe519374f
3
  size 4330865200
model-00004-of-00004.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:1c2667bb1def9db62c2af9c1447ef43fc4cafcaf67b8c9052c0ed695781a75dd
3
  size 1089994880
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:de6f7ae8b22a48abeb54e5972dc2e6f5fd30dabec878c16d8a23bd5b13eda572
3
  size 1089994880
special_tokens_map.json CHANGED
@@ -15,7 +15,7 @@
15
  "<|video_pad|>"
16
  ],
17
  "eos_token": {
18
- "content": "<|endoftext|>",
19
  "lstrip": false,
20
  "normalized": false,
21
  "rstrip": false,
 
15
  "<|video_pad|>"
16
  ],
17
  "eos_token": {
18
+ "content": "<|im_end|>",
19
  "lstrip": false,
20
  "normalized": false,
21
  "rstrip": false,
tokenizer_config.json CHANGED
@@ -195,9 +195,9 @@
195
  "<|video_pad|>"
196
  ],
197
  "bos_token": null,
198
- "chat_template": "{{ bos_token }}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful AI Assistant that provides well-reasoned and detailed responses. You first think about the reasoning process as an internal monologue and then provide the user with the answer. Respond in the following format: <think>\n...\n</think>\n<answer>\n...\n</answer><|im_end|>\n<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n' }}{% elif message['role'] == 'system' %}{{ '<|im_start|>system\n' + message['content'] + '<|im_end|>\n' }}{% elif message['role'] == 'user' %}{{ '<|im_start|>user\n' + message['content'] + '<|im_end|>' + '\n' }}{% elif message['role'] == 'assistant' %}{% if not loop.last %}{{ '<|im_start|>assistant\n' + message['content'] + '<|im_end|>' + '\n' + eos_token + '\n' }}{% else %}{{ '<|im_start|>assistant\n' + message['content'] + '<|im_end|>' + '\n' + eos_token }}{% endif %}{% endif %}{% if loop.last and add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}{% endfor %}",
199
  "clean_up_tokenization_spaces": false,
200
- "eos_token": "<|endoftext|>",
201
  "errors": "replace",
202
  "extra_special_tokens": {},
203
  "model_max_length": 131072,
 
195
  "<|video_pad|>"
196
  ],
197
  "bos_token": null,
198
+ "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'Please reason step by step, and put your final answer within \\\\boxed{}.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nPlease reason step by step, and put your final answer within \\\\boxed{}.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
199
  "clean_up_tokenization_spaces": false,
200
+ "eos_token": "<|im_end|>",
201
  "errors": "replace",
202
  "extra_special_tokens": {},
203
  "model_max_length": 131072,
train_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
  "total_flos": 0.0,
3
- "train_loss": 0.028255671029910445,
4
- "train_runtime": 36935.2831,
5
  "train_samples": 7500,
6
- "train_samples_per_second": 0.203,
7
- "train_steps_per_second": 0.001
8
  }
 
1
  {
2
  "total_flos": 0.0,
3
+ "train_loss": 0.1694948914914559,
4
+ "train_runtime": 74169.3594,
5
  "train_samples": 7500,
6
+ "train_samples_per_second": 0.101,
7
+ "train_steps_per_second": 0.002
8
  }
trainer_state.json CHANGED
@@ -2,258 +2,918 @@
2
  "best_global_step": null,
3
  "best_metric": null,
4
  "best_model_checkpoint": null,
5
- "epoch": 0.9898666666666667,
6
  "eval_steps": 500,
7
- "global_step": 29,
8
  "is_hyper_param_search": false,
9
  "is_local_process_zero": true,
10
  "is_world_process_zero": true,
11
  "log_history": [
12
  {
13
  "clip_ratio": 0.0,
14
- "completion_length": 609.2392578125,
15
- "epoch": 0.034133333333333335,
16
- "grad_norm": 0.23621266719831985,
17
  "kl": 0.0,
18
- "learning_rate": 1e-06,
19
- "loss": -0.0026,
20
- "num_tokens": 785357.0,
21
- "reward": 0.646484375,
22
- "reward_std": 0.2832682034932077,
23
- "rewards/accuracy_reward": 0.646484375,
24
  "rewards/format_reward": 0.0,
25
  "step": 1
26
  },
27
  {
28
  "clip_ratio": 0.0,
29
- "completion_length": 623.9384765625,
30
- "epoch": 0.06826666666666667,
31
- "grad_norm": 0.29521809256012294,
32
  "kl": 0.0,
33
- "learning_rate": 2e-06,
34
- "loss": 0.0061,
35
- "num_tokens": 1593058.0,
36
- "reward": 0.6142578125,
37
- "reward_std": 0.295451024081558,
38
- "rewards/accuracy_reward": 0.6142578125,
39
  "rewards/format_reward": 0.0,
40
  "step": 2
41
  },
42
  {
43
  "clip_ratio": 0.0,
44
- "completion_length": 598.8173828125,
45
- "epoch": 0.13653333333333334,
46
- "grad_norm": 0.42773393862897524,
47
- "kl": 0.0004331320524215698,
48
- "learning_rate": 2.989063311147081e-06,
49
- "loss": 0.0084,
50
- "num_tokens": 3136920.0,
51
- "reward": 0.630859375,
52
- "reward_std": 0.29506791406311095,
53
- "rewards/accuracy_reward": 0.630859375,
54
  "rewards/format_reward": 0.0,
55
  "step": 4
56
  },
57
  {
58
  "clip_ratio": 0.0,
59
- "completion_length": 602.5595703125,
60
- "epoch": 0.2048,
61
- "grad_norm": 0.17771809594185137,
62
- "kl": 0.001168280839920044,
63
- "learning_rate": 2.9025243640281224e-06,
64
- "loss": 0.0428,
65
- "num_tokens": 4677534.0,
66
- "reward": 0.73291015625,
67
- "reward_std": 0.23434827150776982,
68
- "rewards/accuracy_reward": 0.73291015625,
69
  "rewards/format_reward": 0.0,
70
  "step": 6
71
  },
72
  {
73
  "clip_ratio": 0.0,
74
- "completion_length": 602.4541015625,
75
- "epoch": 0.2730666666666667,
76
- "grad_norm": 0.11255873766865199,
77
- "kl": 0.0025081783533096313,
78
- "learning_rate": 2.7344757988404844e-06,
79
- "loss": 0.0544,
80
- "num_tokens": 6229636.0,
81
- "reward": 0.73974609375,
82
- "reward_std": 0.21338723483495414,
83
- "rewards/accuracy_reward": 0.73974609375,
84
  "rewards/format_reward": 0.0,
85
  "step": 8
86
  },
87
  {
88
  "clip_ratio": 0.0,
89
- "completion_length": 604.98681640625,
90
- "epoch": 0.3413333333333333,
91
- "grad_norm": 0.06599060323311819,
92
- "kl": 0.002334892749786377,
93
- "learning_rate": 2.4946839873611927e-06,
94
- "loss": 0.0419,
95
- "num_tokens": 7784865.0,
96
- "reward": 0.75830078125,
97
- "reward_std": 0.17949885036796331,
98
- "rewards/accuracy_reward": 0.75830078125,
99
  "rewards/format_reward": 0.0,
100
  "step": 10
101
  },
102
  {
103
  "clip_ratio": 0.0,
104
- "completion_length": 609.39794921875,
105
- "epoch": 0.4096,
106
- "grad_norm": 0.06593463513171627,
107
- "kl": 0.0026736706495285034,
108
- "learning_rate": 2.1970847580656528e-06,
109
- "loss": 0.0326,
110
- "num_tokens": 9351732.0,
111
- "reward": 0.7705078125,
112
- "reward_std": 0.16446730284951627,
113
- "rewards/accuracy_reward": 0.7705078125,
114
  "rewards/format_reward": 0.0,
115
  "step": 12
116
  },
117
  {
118
  "clip_ratio": 0.0,
119
- "completion_length": 598.2216796875,
120
- "epoch": 0.47786666666666666,
121
- "grad_norm": 0.06574801507589917,
122
- "kl": 0.003045812249183655,
123
- "learning_rate": 1.8589734964313368e-06,
124
- "loss": 0.0238,
125
- "num_tokens": 10890530.0,
126
- "reward": 0.7509765625,
127
- "reward_std": 0.15395715064369142,
128
- "rewards/accuracy_reward": 0.7509765625,
129
  "rewards/format_reward": 0.0,
130
  "step": 14
131
  },
132
  {
133
  "clip_ratio": 0.0,
134
- "completion_length": 612.27392578125,
135
- "epoch": 0.5461333333333334,
136
- "grad_norm": 0.07737476341941271,
137
- "kl": 0.003218412399291992,
138
- "learning_rate": 1.5e-06,
139
- "loss": 0.0251,
140
- "num_tokens": 12469023.0,
141
- "reward": 0.7412109375,
142
- "reward_std": 0.14749347674660385,
143
- "rewards/accuracy_reward": 0.7412109375,
144
  "rewards/format_reward": 0.0,
145
  "step": 16
146
  },
147
  {
148
  "clip_ratio": 0.0,
149
- "completion_length": 598.642578125,
150
- "epoch": 0.6144,
151
- "grad_norm": 0.07278656613203825,
152
- "kl": 0.0029258430004119873,
153
- "learning_rate": 1.141026503568664e-06,
154
- "loss": 0.0356,
155
- "num_tokens": 14024751.0,
156
- "reward": 0.73974609375,
157
- "reward_std": 0.16665246314369142,
158
- "rewards/accuracy_reward": 0.73974609375,
159
  "rewards/format_reward": 0.0,
160
  "step": 18
161
  },
162
  {
163
  "clip_ratio": 0.0,
164
- "completion_length": 592.80224609375,
165
- "epoch": 0.6826666666666666,
166
- "grad_norm": 0.075280235931183,
167
- "kl": 0.0033763498067855835,
168
- "learning_rate": 8.029152419343472e-07,
169
- "loss": 0.0337,
170
- "num_tokens": 15557946.0,
171
- "reward": 0.76513671875,
172
- "reward_std": 0.16409503924660385,
173
- "rewards/accuracy_reward": 0.76513671875,
174
  "rewards/format_reward": 0.0,
175
  "step": 20
176
  },
177
  {
178
  "clip_ratio": 0.0,
179
- "completion_length": 609.025390625,
180
- "epoch": 0.7509333333333333,
181
- "grad_norm": 0.05918406556315966,
182
- "kl": 0.0036567747592926025,
183
- "learning_rate": 5.053160126388076e-07,
184
- "loss": 0.0227,
185
- "num_tokens": 17129102.0,
186
- "reward": 0.7431640625,
187
- "reward_std": 0.15508478786796331,
188
- "rewards/accuracy_reward": 0.74462890625,
189
  "rewards/format_reward": 0.0,
190
  "step": 22
191
  },
192
  {
193
  "clip_ratio": 0.0,
194
- "completion_length": 603.46875,
195
- "epoch": 0.8192,
196
- "grad_norm": 0.054654929027731385,
197
- "kl": 0.0032880455255508423,
198
- "learning_rate": 2.6552420115951547e-07,
199
- "loss": 0.0254,
200
- "num_tokens": 18693822.0,
201
- "reward": 0.74755859375,
202
- "reward_std": 0.14907433814369142,
203
- "rewards/accuracy_reward": 0.74853515625,
204
  "rewards/format_reward": 0.0,
205
  "step": 24
206
  },
207
  {
208
  "clip_ratio": 0.0,
209
- "completion_length": 605.34716796875,
210
- "epoch": 0.8874666666666666,
211
- "grad_norm": 0.1188197019666417,
212
- "kl": 0.0029678642749786377,
213
- "learning_rate": 9.747563597187792e-08,
214
- "loss": 0.0229,
215
- "num_tokens": 20251341.0,
216
- "reward": 0.76611328125,
217
- "reward_std": 0.14734240202233195,
218
- "rewards/accuracy_reward": 0.76611328125,
219
  "rewards/format_reward": 0.0,
220
  "step": 26
221
  },
222
  {
223
  "clip_ratio": 0.0,
224
- "completion_length": 594.63916015625,
225
- "epoch": 0.9557333333333333,
226
- "grad_norm": 0.06119972355000096,
227
- "kl": 0.0031557083129882812,
228
- "learning_rate": 1.093668885291904e-08,
229
- "loss": 0.0283,
230
- "num_tokens": 21794738.0,
231
- "reward": 0.7734375,
232
- "reward_std": 0.15282951341941953,
233
- "rewards/accuracy_reward": 0.7734375,
234
  "rewards/format_reward": 0.0,
235
  "step": 28
236
  },
237
  {
238
  "clip_ratio": 0.0,
239
- "completion_length": 595.41796875,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
240
  "epoch": 0.9898666666666667,
241
- "kl": 0.0034178495407104492,
242
- "num_tokens": 22556823.0,
243
- "reward": 0.7607421875,
244
- "reward_std": 0.15357404062524438,
245
- "rewards/accuracy_reward": 0.7607421875,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
246
  "rewards/format_reward": 0.0,
247
- "step": 29,
248
  "total_flos": 0.0,
249
- "train_loss": 0.028255671029910445,
250
- "train_runtime": 36935.2831,
251
- "train_samples_per_second": 0.203,
252
- "train_steps_per_second": 0.001
253
  }
254
  ],
255
  "logging_steps": 2,
256
- "max_steps": 29,
257
  "num_input_tokens_seen": 0,
258
  "num_train_epochs": 1,
259
  "save_steps": 500,
 
2
  "best_global_step": null,
3
  "best_metric": null,
4
  "best_model_checkpoint": null,
5
+ "epoch": 0.9984,
6
  "eval_steps": 500,
7
+ "global_step": 117,
8
  "is_hyper_param_search": false,
9
  "is_local_process_zero": true,
10
  "is_world_process_zero": true,
11
  "log_history": [
12
  {
13
  "clip_ratio": 0.0,
14
+ "completion_length": 635.126953125,
15
+ "epoch": 0.008533333333333334,
16
+ "grad_norm": 0.6395311468390221,
17
  "kl": 0.0,
18
+ "learning_rate": 2.5e-07,
19
+ "loss": 0.0603,
20
+ "num_tokens": 406601.0,
21
+ "reward": 0.6796875,
22
+ "reward_std": 0.17794983368366957,
23
+ "rewards/accuracy_reward": 0.6796875,
24
  "rewards/format_reward": 0.0,
25
  "step": 1
26
  },
27
  {
28
  "clip_ratio": 0.0,
29
+ "completion_length": 568.509765625,
30
+ "epoch": 0.017066666666666667,
31
+ "grad_norm": 0.3978739586526697,
32
  "kl": 0.0,
33
+ "learning_rate": 5e-07,
34
+ "loss": 0.0391,
35
+ "num_tokens": 776134.0,
36
+ "reward": 0.73046875,
37
+ "reward_std": 0.17123176017776132,
38
+ "rewards/accuracy_reward": 0.73046875,
39
  "rewards/format_reward": 0.0,
40
  "step": 2
41
  },
42
  {
43
  "clip_ratio": 0.0,
44
+ "completion_length": 578.5009765625,
45
+ "epoch": 0.034133333333333335,
46
+ "grad_norm": 0.2928130055744145,
47
+ "kl": 1.120672095566988e-05,
48
+ "learning_rate": 1e-06,
49
+ "loss": 0.0263,
50
+ "num_tokens": 1531639.0,
51
+ "reward": 0.68359375,
52
+ "reward_std": 0.13874951610341668,
53
+ "rewards/accuracy_reward": 0.68359375,
54
  "rewards/format_reward": 0.0,
55
  "step": 4
56
  },
57
  {
58
  "clip_ratio": 0.0,
59
+ "completion_length": 615.7861328125,
60
+ "epoch": 0.0512,
61
+ "grad_norm": 0.38001767737083486,
62
+ "kl": 7.296388503164053e-06,
63
+ "learning_rate": 1.5e-06,
64
+ "loss": 0.0361,
65
+ "num_tokens": 2334764.0,
66
+ "reward": 0.642578125,
67
+ "reward_std": 0.22008429956622422,
68
+ "rewards/accuracy_reward": 0.642578125,
69
  "rewards/format_reward": 0.0,
70
  "step": 6
71
  },
72
  {
73
  "clip_ratio": 0.0,
74
+ "completion_length": 606.6162109375,
75
+ "epoch": 0.06826666666666667,
76
+ "grad_norm": 0.36726993629552374,
77
+ "kl": 1.181039260700345e-05,
78
+ "learning_rate": 2e-06,
79
+ "loss": 0.0446,
80
+ "num_tokens": 3120955.0,
81
+ "reward": 0.67578125,
82
+ "reward_std": 0.18526801373809576,
83
+ "rewards/accuracy_reward": 0.67578125,
84
  "rewards/format_reward": 0.0,
85
  "step": 8
86
  },
87
  {
88
  "clip_ratio": 0.0,
89
+ "completion_length": 587.7744140625,
90
+ "epoch": 0.08533333333333333,
91
+ "grad_norm": 0.5438420318338805,
92
+ "kl": 0.00024004688020795584,
93
+ "learning_rate": 2.5e-06,
94
+ "loss": 0.0401,
95
+ "num_tokens": 3883788.0,
96
+ "reward": 0.7041015625,
97
+ "reward_std": 0.15495382226072252,
98
+ "rewards/accuracy_reward": 0.7041015625,
99
  "rewards/format_reward": 0.0,
100
  "step": 10
101
  },
102
  {
103
  "clip_ratio": 0.0,
104
+ "completion_length": 567.94140625,
105
+ "epoch": 0.1024,
106
+ "grad_norm": 0.3374078187837519,
107
+ "kl": 0.0005977721302770078,
108
+ "learning_rate": 3e-06,
109
+ "loss": 0.03,
110
+ "num_tokens": 4627856.0,
111
+ "reward": 0.7080078125,
112
+ "reward_std": 0.14151287800632417,
113
+ "rewards/accuracy_reward": 0.7080078125,
114
  "rewards/format_reward": 0.0,
115
  "step": 12
116
  },
117
  {
118
  "clip_ratio": 0.0,
119
+ "completion_length": 586.3916015625,
120
+ "epoch": 0.11946666666666667,
121
+ "grad_norm": 0.5380156747856304,
122
+ "kl": 0.005719492677599192,
123
+ "learning_rate": 2.9973151946516025e-06,
124
+ "loss": 0.06,
125
+ "num_tokens": 5372441.0,
126
+ "reward": 0.7119140625,
127
+ "reward_std": 0.18398740980774164,
128
+ "rewards/accuracy_reward": 0.7119140625,
129
  "rewards/format_reward": 0.0,
130
  "step": 14
131
  },
132
  {
133
  "clip_ratio": 0.0,
134
+ "completion_length": 613.46484375,
135
+ "epoch": 0.13653333333333334,
136
+ "grad_norm": 0.7673623447856024,
137
+ "kl": 0.015465203672647476,
138
+ "learning_rate": 2.989270389512756e-06,
139
+ "loss": 0.0697,
140
+ "num_tokens": 6168029.0,
141
+ "reward": 0.6435546875,
142
+ "reward_std": 0.2058832028415054,
143
+ "rewards/accuracy_reward": 0.6435546875,
144
  "rewards/format_reward": 0.0,
145
  "step": 16
146
  },
147
  {
148
  "clip_ratio": 0.0,
149
+ "completion_length": 566.7099609375,
150
+ "epoch": 0.1536,
151
+ "grad_norm": 0.8551080207596556,
152
+ "kl": 0.02153320051729679,
153
+ "learning_rate": 2.9758943828979446e-06,
154
+ "loss": 0.0669,
155
+ "num_tokens": 6893764.0,
156
+ "reward": 0.703125,
157
+ "reward_std": 0.21476810285821557,
158
+ "rewards/accuracy_reward": 0.703125,
159
  "rewards/format_reward": 0.0,
160
  "step": 18
161
  },
162
  {
163
  "clip_ratio": 0.0,
164
+ "completion_length": 617.9345703125,
165
+ "epoch": 0.17066666666666666,
166
+ "grad_norm": 2.416498946611759,
167
+ "kl": 0.04414602927863598,
168
+ "learning_rate": 2.957235057439301e-06,
169
+ "loss": 0.0841,
170
+ "num_tokens": 7688649.0,
171
+ "reward": 0.6337890625,
172
+ "reward_std": 0.20062413928098977,
173
+ "rewards/accuracy_reward": 0.6337890625,
174
  "rewards/format_reward": 0.0,
175
  "step": 20
176
  },
177
  {
178
  "clip_ratio": 0.0,
179
+ "completion_length": 647.6904296875,
180
+ "epoch": 0.18773333333333334,
181
+ "grad_norm": 1.3063605057043102,
182
+ "kl": 0.07265654765069485,
183
+ "learning_rate": 2.933359208679211e-06,
184
+ "loss": 0.0894,
185
+ "num_tokens": 8507764.0,
186
+ "reward": 0.6083984375,
187
+ "reward_std": 0.2147587512154132,
188
+ "rewards/accuracy_reward": 0.6083984375,
189
  "rewards/format_reward": 0.0,
190
  "step": 22
191
  },
192
  {
193
  "clip_ratio": 0.0,
194
+ "completion_length": 577.3544921875,
195
+ "epoch": 0.2048,
196
+ "grad_norm": 0.9576537994468717,
197
+ "kl": 0.0842108279466629,
198
+ "learning_rate": 2.904352305959606e-06,
199
+ "loss": 0.1019,
200
+ "num_tokens": 9248695.0,
201
+ "reward": 0.7001953125,
202
+ "reward_std": 0.2201498057693243,
203
+ "rewards/accuracy_reward": 0.7001953125,
204
  "rewards/format_reward": 0.0,
205
  "step": 24
206
  },
207
  {
208
  "clip_ratio": 0.0,
209
+ "completion_length": 617.2255859375,
210
+ "epoch": 0.22186666666666666,
211
+ "grad_norm": 1.0236250726018012,
212
+ "kl": 0.1061122715473175,
213
+ "learning_rate": 2.8703181864639013e-06,
214
+ "loss": 0.1201,
215
+ "num_tokens": 10033030.0,
216
+ "reward": 0.6640625,
217
+ "reward_std": 0.25549834687262774,
218
+ "rewards/accuracy_reward": 0.6640625,
219
  "rewards/format_reward": 0.0,
220
  "step": 26
221
  },
222
  {
223
  "clip_ratio": 0.0,
224
+ "completion_length": 624.8525390625,
225
+ "epoch": 0.23893333333333333,
226
+ "grad_norm": 0.7738985933722767,
227
+ "kl": 0.1274673491716385,
228
+ "learning_rate": 2.8313786835068315e-06,
229
+ "loss": 0.1069,
230
+ "num_tokens": 10825831.0,
231
+ "reward": 0.6279296875,
232
+ "reward_std": 0.22281860560178757,
233
+ "rewards/accuracy_reward": 0.6279296875,
234
  "rewards/format_reward": 0.0,
235
  "step": 28
236
  },
237
  {
238
  "clip_ratio": 0.0,
239
+ "completion_length": 607.80859375,
240
+ "epoch": 0.256,
241
+ "grad_norm": 2.053309280558149,
242
+ "kl": 0.1347993239760399,
243
+ "learning_rate": 2.7876731904027993e-06,
244
+ "loss": 0.1112,
245
+ "num_tokens": 11625699.0,
246
+ "reward": 0.634765625,
247
+ "reward_std": 0.22420434933155775,
248
+ "rewards/accuracy_reward": 0.634765625,
249
+ "rewards/format_reward": 0.0,
250
+ "step": 30
251
+ },
252
+ {
253
+ "clip_ratio": 0.0,
254
+ "completion_length": 603.4423828125,
255
+ "epoch": 0.2730666666666667,
256
+ "grad_norm": 4.067058887496009,
257
+ "kl": 0.16801568865776062,
258
+ "learning_rate": 2.7393581614739926e-06,
259
+ "loss": 0.1299,
260
+ "num_tokens": 12397456.0,
261
+ "reward": 0.654296875,
262
+ "reward_std": 0.27433712710626423,
263
+ "rewards/accuracy_reward": 0.654296875,
264
+ "rewards/format_reward": 0.0,
265
+ "step": 32
266
+ },
267
+ {
268
+ "clip_ratio": 0.0,
269
+ "completion_length": 627.7119140625,
270
+ "epoch": 0.29013333333333335,
271
+ "grad_norm": 1.3847909943122017,
272
+ "kl": 0.19360647350549698,
273
+ "learning_rate": 2.6866065519845123e-06,
274
+ "loss": 0.1096,
275
+ "num_tokens": 13200929.0,
276
+ "reward": 0.634765625,
277
+ "reward_std": 0.21354426653124392,
278
+ "rewards/accuracy_reward": 0.634765625,
279
+ "rewards/format_reward": 0.0,
280
+ "step": 34
281
+ },
282
+ {
283
+ "clip_ratio": 0.0,
284
+ "completion_length": 630.40625,
285
+ "epoch": 0.3072,
286
+ "grad_norm": 0.7646338265276826,
287
+ "kl": 0.1692635715007782,
288
+ "learning_rate": 2.6296071990054165e-06,
289
+ "loss": 0.1261,
290
+ "num_tokens": 14006033.0,
291
+ "reward": 0.6416015625,
292
+ "reward_std": 0.2696962603367865,
293
+ "rewards/accuracy_reward": 0.6416015625,
294
+ "rewards/format_reward": 0.0,
295
+ "step": 36
296
+ },
297
+ {
298
+ "clip_ratio": 0.0,
299
+ "completion_length": 629.939453125,
300
+ "epoch": 0.32426666666666665,
301
+ "grad_norm": 1.6400416690599355,
302
+ "kl": 0.22570940852165222,
303
+ "learning_rate": 2.5685641454270174e-06,
304
+ "loss": 0.1629,
305
+ "num_tokens": 14805347.0,
306
+ "reward": 0.62890625,
307
+ "reward_std": 0.260196712333709,
308
+ "rewards/accuracy_reward": 0.62890625,
309
+ "rewards/format_reward": 0.0,
310
+ "step": 38
311
+ },
312
+ {
313
+ "clip_ratio": 0.0,
314
+ "completion_length": 590.64453125,
315
+ "epoch": 0.3413333333333333,
316
+ "grad_norm": 1.9814122678587998,
317
+ "kl": 0.20644378662109375,
318
+ "learning_rate": 2.5036959095382875e-06,
319
+ "loss": 0.1376,
320
+ "num_tokens": 15568079.0,
321
+ "reward": 0.6396484375,
322
+ "reward_std": 0.2311337033752352,
323
+ "rewards/accuracy_reward": 0.6396484375,
324
+ "rewards/format_reward": 0.0,
325
+ "step": 40
326
+ },
327
+ {
328
+ "clip_ratio": 0.0,
329
+ "completion_length": 624.5517578125,
330
+ "epoch": 0.3584,
331
+ "grad_norm": 0.7992402392720819,
332
+ "kl": 0.20878393948078156,
333
+ "learning_rate": 2.4352347027881005e-06,
334
+ "loss": 0.1235,
335
+ "num_tokens": 16374948.0,
336
+ "reward": 0.6328125,
337
+ "reward_std": 0.24743947107344866,
338
+ "rewards/accuracy_reward": 0.6328125,
339
+ "rewards/format_reward": 0.0,
340
+ "step": 42
341
+ },
342
+ {
343
+ "clip_ratio": 0.0,
344
+ "completion_length": 616.9150390625,
345
+ "epoch": 0.37546666666666667,
346
+ "grad_norm": 1.0209831895837471,
347
+ "kl": 0.29173046350479126,
348
+ "learning_rate": 2.3634255985285104e-06,
349
+ "loss": 0.166,
350
+ "num_tokens": 17157997.0,
351
+ "reward": 0.640625,
352
+ "reward_std": 0.2668769913725555,
353
+ "rewards/accuracy_reward": 0.640625,
354
+ "rewards/format_reward": 0.0,
355
+ "step": 44
356
+ },
357
+ {
358
+ "clip_ratio": 0.0,
359
+ "completion_length": 655.28125,
360
+ "epoch": 0.39253333333333335,
361
+ "grad_norm": 2.3877680127484027,
362
+ "kl": 0.38541412353515625,
363
+ "learning_rate": 2.288525654715757e-06,
364
+ "loss": 0.2105,
365
+ "num_tokens": 17986773.0,
366
+ "reward": 0.578125,
367
+ "reward_std": 0.318851436721161,
368
+ "rewards/accuracy_reward": 0.578125,
369
+ "rewards/format_reward": 0.0,
370
+ "step": 46
371
+ },
372
+ {
373
+ "clip_ratio": 0.0,
374
+ "completion_length": 658.8642578125,
375
+ "epoch": 0.4096,
376
+ "grad_norm": 1.1534735045296605,
377
+ "kl": 0.5227391719818115,
378
+ "learning_rate": 2.210802993709498e-06,
379
+ "loss": 0.2131,
380
+ "num_tokens": 18822666.0,
381
+ "reward": 0.5625,
382
+ "reward_std": 0.2897139354608953,
383
+ "rewards/accuracy_reward": 0.5625,
384
+ "rewards/format_reward": 0.0,
385
+ "step": 48
386
+ },
387
+ {
388
+ "clip_ratio": 0.0,
389
+ "completion_length": 686.6533203125,
390
+ "epoch": 0.4266666666666667,
391
+ "grad_norm": 0.8115361840628914,
392
+ "kl": 0.6134325265884399,
393
+ "learning_rate": 2.1305358424643485e-06,
394
+ "loss": 0.1922,
395
+ "num_tokens": 19682471.0,
396
+ "reward": 0.4873046875,
397
+ "reward_std": 0.2924760712776333,
398
+ "rewards/accuracy_reward": 0.4873046875,
399
+ "rewards/format_reward": 0.0,
400
+ "step": 50
401
+ },
402
+ {
403
+ "clip_ratio": 0.0,
404
+ "completion_length": 677.859375,
405
+ "epoch": 0.4437333333333333,
406
+ "grad_norm": 2.335343150105781,
407
+ "kl": 0.6195580959320068,
408
+ "learning_rate": 2.048011536549593e-06,
409
+ "loss": 0.2115,
410
+ "num_tokens": 20534495.0,
411
+ "reward": 0.4921875,
412
+ "reward_std": 0.33811459480784833,
413
+ "rewards/accuracy_reward": 0.4921875,
414
+ "rewards/format_reward": 0.0,
415
+ "step": 52
416
+ },
417
+ {
418
+ "clip_ratio": 0.0,
419
+ "completion_length": 695.298828125,
420
+ "epoch": 0.4608,
421
+ "grad_norm": 0.936446069249802,
422
+ "kl": 0.8193651437759399,
423
+ "learning_rate": 1.963525491562421e-06,
424
+ "loss": 0.198,
425
+ "num_tokens": 21401217.0,
426
+ "reward": 0.466796875,
427
+ "reward_std": 0.3250986794009805,
428
+ "rewards/accuracy_reward": 0.466796875,
429
+ "rewards/format_reward": 0.0,
430
+ "step": 54
431
+ },
432
+ {
433
+ "clip_ratio": 0.0,
434
+ "completion_length": 670.49609375,
435
+ "epoch": 0.47786666666666666,
436
+ "grad_norm": 1.2585716542171583,
437
+ "kl": 0.8083813190460205,
438
+ "learning_rate": 1.877380145616763e-06,
439
+ "loss": 0.2072,
440
+ "num_tokens": 22245781.0,
441
+ "reward": 0.48046875,
442
+ "reward_std": 0.3280505524016917,
443
+ "rewards/accuracy_reward": 0.48046875,
444
+ "rewards/format_reward": 0.0,
445
+ "step": 56
446
+ },
447
+ {
448
+ "clip_ratio": 0.0,
449
+ "completion_length": 682.578125,
450
+ "epoch": 0.49493333333333334,
451
+ "grad_norm": 1.730566930595855,
452
+ "kl": 1.0304815769195557,
453
+ "learning_rate": 1.7898838766933299e-06,
454
+ "loss": 0.2221,
455
+ "num_tokens": 23100117.0,
456
+ "reward": 0.4677734375,
457
+ "reward_std": 0.34290964691899717,
458
+ "rewards/accuracy_reward": 0.4677734375,
459
+ "rewards/format_reward": 0.0,
460
+ "step": 58
461
+ },
462
+ {
463
+ "clip_ratio": 0.0,
464
+ "completion_length": 693.1591796875,
465
+ "epoch": 0.512,
466
+ "grad_norm": 1.438316022085548,
467
+ "kl": 0.9743777513504028,
468
+ "learning_rate": 1.7013498987264833e-06,
469
+ "loss": 0.1934,
470
+ "num_tokens": 23971624.0,
471
+ "reward": 0.455078125,
472
+ "reward_std": 0.31845546374097466,
473
+ "rewards/accuracy_reward": 0.455078125,
474
+ "rewards/format_reward": 0.0,
475
+ "step": 60
476
+ },
477
+ {
478
+ "clip_ratio": 0.0,
479
+ "completion_length": 674.126953125,
480
+ "epoch": 0.5290666666666667,
481
+ "grad_norm": 0.7991321837464155,
482
+ "kl": 1.1657259464263916,
483
+ "learning_rate": 1.6120951403796365e-06,
484
+ "loss": 0.2183,
485
+ "num_tokens": 24829178.0,
486
+ "reward": 0.4619140625,
487
+ "reward_std": 0.32980443933047354,
488
+ "rewards/accuracy_reward": 0.4619140625,
489
+ "rewards/format_reward": 0.0,
490
+ "step": 62
491
+ },
492
+ {
493
+ "clip_ratio": 0.0,
494
+ "completion_length": 683.255859375,
495
+ "epoch": 0.5461333333333334,
496
+ "grad_norm": 1.252900556331916,
497
+ "kl": 1.1991257667541504,
498
+ "learning_rate": 1.5224391105228955e-06,
499
+ "loss": 0.2287,
500
+ "num_tokens": 25693608.0,
501
+ "reward": 0.4541015625,
502
+ "reward_std": 0.3399870772846043,
503
+ "rewards/accuracy_reward": 0.4541015625,
504
+ "rewards/format_reward": 0.0,
505
+ "step": 64
506
+ },
507
+ {
508
+ "clip_ratio": 0.0,
509
+ "completion_length": 682.7490234375,
510
+ "epoch": 0.5632,
511
+ "grad_norm": 1.0658219410533047,
512
+ "kl": 1.0920262336730957,
513
+ "learning_rate": 1.4327027544742282e-06,
514
+ "loss": 0.1729,
515
+ "num_tokens": 26565695.0,
516
+ "reward": 0.4716796875,
517
+ "reward_std": 0.29094083700329065,
518
+ "rewards/accuracy_reward": 0.4716796875,
519
+ "rewards/format_reward": 0.0,
520
+ "step": 66
521
+ },
522
+ {
523
+ "clip_ratio": 0.0,
524
+ "completion_length": 679.49609375,
525
+ "epoch": 0.5802666666666667,
526
+ "grad_norm": 0.7213359939486753,
527
+ "kl": 1.1640419960021973,
528
+ "learning_rate": 1.3432073050985201e-06,
529
+ "loss": 0.233,
530
+ "num_tokens": 27428483.0,
531
+ "reward": 0.42578125,
532
+ "reward_std": 0.3486728884745389,
533
+ "rewards/accuracy_reward": 0.42578125,
534
+ "rewards/format_reward": 0.0,
535
+ "step": 68
536
+ },
537
+ {
538
+ "clip_ratio": 0.0,
539
+ "completion_length": 719.8935546875,
540
+ "epoch": 0.5973333333333334,
541
+ "grad_norm": 1.141153692198079,
542
+ "kl": 1.179184913635254,
543
+ "learning_rate": 1.2542731328772936e-06,
544
+ "loss": 0.1907,
545
+ "num_tokens": 28320078.0,
546
+ "reward": 0.4365234375,
547
+ "reward_std": 0.3560307021252811,
548
+ "rewards/accuracy_reward": 0.4365234375,
549
+ "rewards/format_reward": 0.0,
550
+ "step": 70
551
+ },
552
+ {
553
+ "clip_ratio": 0.0,
554
+ "completion_length": 663.5009765625,
555
+ "epoch": 0.6144,
556
+ "grad_norm": 0.6721068419339931,
557
+ "kl": 1.0740742683410645,
558
+ "learning_rate": 1.1662185990655286e-06,
559
+ "loss": 0.1856,
560
+ "num_tokens": 29164559.0,
561
+ "reward": 0.45703125,
562
+ "reward_std": 0.3046431930270046,
563
+ "rewards/accuracy_reward": 0.45703125,
564
+ "rewards/format_reward": 0.0,
565
+ "step": 72
566
+ },
567
+ {
568
+ "clip_ratio": 0.0,
569
+ "completion_length": 659.466796875,
570
+ "epoch": 0.6314666666666666,
571
+ "grad_norm": 1.0601082808384605,
572
+ "kl": 1.3345909118652344,
573
+ "learning_rate": 1.079358916040996e-06,
574
+ "loss": 0.2408,
575
+ "num_tokens": 29999605.0,
576
+ "reward": 0.482421875,
577
+ "reward_std": 0.35783175751566887,
578
+ "rewards/accuracy_reward": 0.482421875,
579
+ "rewards/format_reward": 0.0,
580
+ "step": 74
581
+ },
582
+ {
583
+ "clip_ratio": 0.0,
584
+ "completion_length": 650.8701171875,
585
+ "epoch": 0.6485333333333333,
586
+ "grad_norm": 0.7261564892244352,
587
+ "kl": 1.3090394735336304,
588
+ "learning_rate": 9.94005018925755e-07,
589
+ "loss": 0.2281,
590
+ "num_tokens": 30830072.0,
591
+ "reward": 0.5,
592
+ "reward_std": 0.3525468213483691,
593
+ "rewards/accuracy_reward": 0.5,
594
+ "rewards/format_reward": 0.0,
595
+ "step": 76
596
+ },
597
+ {
598
+ "clip_ratio": 0.0,
599
+ "completion_length": 660.0498046875,
600
+ "epoch": 0.6656,
601
+ "grad_norm": 0.809244012044935,
602
+ "kl": 1.414804220199585,
603
+ "learning_rate": 9.104624525191147e-07,
604
+ "loss": 0.229,
605
+ "num_tokens": 31660627.0,
606
+ "reward": 0.4833984375,
607
+ "reward_std": 0.3342659214977175,
608
+ "rewards/accuracy_reward": 0.4833984375,
609
+ "rewards/format_reward": 0.0,
610
+ "step": 78
611
+ },
612
+ {
613
+ "clip_ratio": 0.0,
614
+ "completion_length": 707.998046875,
615
+ "epoch": 0.6826666666666666,
616
+ "grad_norm": 0.829618860187009,
617
+ "kl": 1.2725417613983154,
618
+ "learning_rate": 8.290302775265509e-07,
619
+ "loss": 0.2243,
620
+ "num_tokens": 32545497.0,
621
+ "reward": 0.44140625,
622
+ "reward_std": 0.33390835602767766,
623
+ "rewards/accuracy_reward": 0.44140625,
624
+ "rewards/format_reward": 0.0,
625
+ "step": 80
626
+ },
627
+ {
628
+ "clip_ratio": 0.0,
629
+ "completion_length": 686.3525390625,
630
+ "epoch": 0.6997333333333333,
631
+ "grad_norm": 1.0692886522584544,
632
+ "kl": 1.46016526222229,
633
+ "learning_rate": 7.500000000000003e-07,
634
+ "loss": 0.2172,
635
+ "num_tokens": 33399938.0,
636
+ "reward": 0.462890625,
637
+ "reward_std": 0.34255110286176205,
638
+ "rewards/accuracy_reward": 0.462890625,
639
+ "rewards/format_reward": 0.0,
640
+ "step": 82
641
+ },
642
+ {
643
+ "clip_ratio": 0.0,
644
+ "completion_length": 681.7529296875,
645
+ "epoch": 0.7168,
646
+ "grad_norm": 0.7824851387467523,
647
+ "kl": 1.6537617444992065,
648
+ "learning_rate": 6.736545278218464e-07,
649
+ "loss": 0.2377,
650
+ "num_tokens": 34254333.0,
651
+ "reward": 0.458984375,
652
+ "reward_std": 0.35577166243456304,
653
+ "rewards/accuracy_reward": 0.458984375,
654
+ "rewards/format_reward": 0.0,
655
+ "step": 84
656
+ },
657
+ {
658
+ "clip_ratio": 0.0,
659
+ "completion_length": 697.927734375,
660
+ "epoch": 0.7338666666666667,
661
+ "grad_norm": 0.6324560657515779,
662
+ "kl": 1.3420374393463135,
663
+ "learning_rate": 6.002671579681295e-07,
664
+ "loss": 0.2057,
665
+ "num_tokens": 35139235.0,
666
+ "reward": 0.4541015625,
667
+ "reward_std": 0.3485010163858533,
668
+ "rewards/accuracy_reward": NaN,
669
+ "rewards/format_reward": 0.0,
670
+ "step": 86
671
+ },
672
+ {
673
+ "clip_ratio": 0.0,
674
+ "completion_length": 667.0712890625,
675
+ "epoch": 0.7509333333333333,
676
+ "grad_norm": 0.7581516198278789,
677
+ "kl": 1.462003469467163,
678
+ "learning_rate": 5.301005981763008e-07,
679
+ "loss": 0.2314,
680
+ "num_tokens": 35991940.0,
681
+ "reward": 0.4755859375,
682
+ "reward_std": 0.3375488743185997,
683
+ "rewards/accuracy_reward": 0.4755859375,
684
+ "rewards/format_reward": 0.0,
685
+ "step": 88
686
+ },
687
+ {
688
+ "clip_ratio": 0.0,
689
+ "completion_length": 651.244140625,
690
+ "epoch": 0.768,
691
+ "grad_norm": 1.149771581664081,
692
+ "kl": 1.4573760032653809,
693
+ "learning_rate": 4.63406026519703e-07,
694
+ "loss": 0.2122,
695
+ "num_tokens": 36824670.0,
696
+ "reward": 0.4892578125,
697
+ "reward_std": 0.3413656740449369,
698
+ "rewards/accuracy_reward": 0.4892578125,
699
+ "rewards/format_reward": 0.0,
700
+ "step": 90
701
+ },
702
+ {
703
+ "clip_ratio": 0.0,
704
+ "completion_length": 670.01171875,
705
+ "epoch": 0.7850666666666667,
706
+ "grad_norm": 0.8650230378477372,
707
+ "kl": 1.3401384353637695,
708
+ "learning_rate": 4.0042219225526084e-07,
709
+ "loss": 0.2158,
710
+ "num_tokens": 37675050.0,
711
+ "reward": 0.4619140625,
712
+ "reward_std": 0.3221384333446622,
713
+ "rewards/accuracy_reward": 0.4619140625,
714
+ "rewards/format_reward": 0.0,
715
+ "step": 92
716
+ },
717
+ {
718
+ "clip_ratio": 0.0,
719
+ "completion_length": 658.0634765625,
720
+ "epoch": 0.8021333333333334,
721
+ "grad_norm": 1.069246045365052,
722
+ "kl": 1.3796547651290894,
723
+ "learning_rate": 3.4137456116310087e-07,
724
+ "loss": 0.2059,
725
+ "num_tokens": 38506451.0,
726
+ "reward": 0.4775390625,
727
+ "reward_std": 0.3411385079380125,
728
+ "rewards/accuracy_reward": 0.4775390625,
729
+ "rewards/format_reward": 0.0,
730
+ "step": 94
731
+ },
732
+ {
733
+ "clip_ratio": 0.0,
734
+ "completion_length": 633.93359375,
735
+ "epoch": 0.8192,
736
+ "grad_norm": 1.3141678752688295,
737
+ "kl": 1.41829252243042,
738
+ "learning_rate": 2.86474508437579e-07,
739
+ "loss": 0.2136,
740
+ "num_tokens": 39325543.0,
741
+ "reward": 0.5146484375,
742
+ "reward_std": 0.3530385824851692,
743
+ "rewards/accuracy_reward": NaN,
744
+ "rewards/format_reward": 0.0,
745
+ "step": 96
746
+ },
747
+ {
748
+ "clip_ratio": 0.0,
749
+ "completion_length": 638.5849609375,
750
+ "epoch": 0.8362666666666667,
751
+ "grad_norm": 0.6225949267416366,
752
+ "kl": 1.382025122642517,
753
+ "learning_rate": 2.3591856201894125e-07,
754
+ "loss": 0.1809,
755
+ "num_tokens": 40142158.0,
756
+ "reward": 0.5078125,
757
+ "reward_std": 0.3463376206345856,
758
+ "rewards/accuracy_reward": 0.5078125,
759
+ "rewards/format_reward": 0.0,
760
+ "step": 98
761
+ },
762
+ {
763
+ "clip_ratio": 0.0,
764
+ "completion_length": 654.8212890625,
765
+ "epoch": 0.8533333333333334,
766
+ "grad_norm": 0.8100698859065342,
767
+ "kl": 1.5549572706222534,
768
+ "learning_rate": 1.8988769907430552e-07,
769
+ "loss": 0.2397,
770
+ "num_tokens": 40968791.0,
771
+ "reward": 0.49609375,
772
+ "reward_std": 0.34113691630773246,
773
+ "rewards/accuracy_reward": 0.49609375,
774
+ "rewards/format_reward": 0.0,
775
+ "step": 100
776
+ },
777
+ {
778
+ "clip_ratio": 0.0,
779
+ "completion_length": 636.75,
780
+ "epoch": 0.8704,
781
+ "grad_norm": 0.7556943680962844,
782
+ "kl": 1.4161872863769531,
783
+ "learning_rate": 1.4854669814637145e-07,
784
+ "loss": 0.2239,
785
+ "num_tokens": 41776423.0,
786
+ "reward": 0.509765625,
787
+ "reward_std": 0.34553979174233973,
788
+ "rewards/accuracy_reward": 0.509765625,
789
+ "rewards/format_reward": 0.0,
790
+ "step": 102
791
+ },
792
+ {
793
+ "clip_ratio": 0.0,
794
+ "completion_length": 680.8701171875,
795
+ "epoch": 0.8874666666666666,
796
+ "grad_norm": 1.864698019362775,
797
+ "kl": 1.522972583770752,
798
+ "learning_rate": 1.1204354928900495e-07,
799
+ "loss": 0.2215,
800
+ "num_tokens": 42634770.0,
801
+ "reward": 0.5244140625,
802
+ "reward_std": 0.37442070548422635,
803
+ "rewards/accuracy_reward": 0.5244140625,
804
+ "rewards/format_reward": 0.0,
805
+ "step": 104
806
+ },
807
+ {
808
+ "clip_ratio": 0.0,
809
+ "completion_length": 641.76171875,
810
+ "epoch": 0.9045333333333333,
811
+ "grad_norm": 0.738823482177991,
812
+ "kl": 1.6065247058868408,
813
+ "learning_rate": 8.050892430125362e-08,
814
+ "loss": 0.2359,
815
+ "num_tokens": 43454382.0,
816
+ "reward": 0.513671875,
817
+ "reward_std": 0.31917500402778387,
818
+ "rewards/accuracy_reward": 0.513671875,
819
+ "rewards/format_reward": 0.0,
820
+ "step": 106
821
+ },
822
+ {
823
+ "clip_ratio": 0.0,
824
+ "completion_length": 614.0791015625,
825
+ "epoch": 0.9216,
826
+ "grad_norm": 0.8114583750166938,
827
+ "kl": 1.5821502208709717,
828
+ "learning_rate": 5.405570895622014e-08,
829
+ "loss": 0.2511,
830
+ "num_tokens": 44243727.0,
831
+ "reward": 0.548828125,
832
+ "reward_std": 0.34129240782931447,
833
+ "rewards/accuracy_reward": 0.548828125,
834
+ "rewards/format_reward": 0.0,
835
+ "step": 108
836
+ },
837
+ {
838
+ "clip_ratio": 0.0,
839
+ "completion_length": 644.2939453125,
840
+ "epoch": 0.9386666666666666,
841
+ "grad_norm": 1.1755921438495844,
842
+ "kl": 1.6895747184753418,
843
+ "learning_rate": 3.277859889929147e-08,
844
+ "loss": 0.2189,
845
+ "num_tokens": 45063404.0,
846
+ "reward": 0.525390625,
847
+ "reward_std": 0.366482344456017,
848
+ "rewards/accuracy_reward": 0.525390625,
849
+ "rewards/format_reward": 0.0,
850
+ "step": 110
851
+ },
852
+ {
853
+ "clip_ratio": 0.0,
854
+ "completion_length": 659.8671875,
855
+ "epoch": 0.9557333333333333,
856
+ "grad_norm": 0.8029884872533015,
857
+ "kl": 1.5845341682434082,
858
+ "learning_rate": 1.6753760662307216e-08,
859
+ "loss": 0.2013,
860
+ "num_tokens": 45907364.0,
861
+ "reward": 0.484375,
862
+ "reward_std": 0.34991508489474654,
863
+ "rewards/accuracy_reward": 0.484375,
864
+ "rewards/format_reward": 0.0,
865
+ "step": 112
866
+ },
867
+ {
868
+ "clip_ratio": 0.0,
869
+ "completion_length": 654.6015625,
870
+ "epoch": 0.9728,
871
+ "grad_norm": 1.0658581526050372,
872
+ "kl": 1.4549345970153809,
873
+ "learning_rate": 6.038559007141398e-09,
874
+ "loss": 0.2538,
875
+ "num_tokens": 46737148.0,
876
+ "reward": 0.5087890625,
877
+ "reward_std": 0.35136694787070155,
878
+ "rewards/accuracy_reward": 0.5087890625,
879
+ "rewards/format_reward": 0.0,
880
+ "step": 114
881
+ },
882
+ {
883
+ "clip_ratio": 0.0,
884
+ "completion_length": 649.0869140625,
885
  "epoch": 0.9898666666666667,
886
+ "grad_norm": 0.9380076341662866,
887
+ "kl": 1.4578795433044434,
888
+ "learning_rate": 6.71351574745016e-10,
889
+ "loss": 0.2334,
890
+ "num_tokens": 47562341.0,
891
+ "reward": 0.5068359375,
892
+ "reward_std": 0.3348612308036536,
893
+ "rewards/accuracy_reward": 0.5068359375,
894
+ "rewards/format_reward": 0.0,
895
+ "step": 116
896
+ },
897
+ {
898
+ "clip_ratio": 0.0,
899
+ "completion_length": 697.40625,
900
+ "epoch": 0.9984,
901
+ "kl": 1.8018455505371094,
902
+ "num_tokens": 47993634.0,
903
+ "reward": 0.4453125,
904
+ "reward_std": 0.38571832375600934,
905
+ "rewards/accuracy_reward": 0.4453125,
906
  "rewards/format_reward": 0.0,
907
+ "step": 117,
908
  "total_flos": 0.0,
909
+ "train_loss": 0.1694948914914559,
910
+ "train_runtime": 74169.3594,
911
+ "train_samples_per_second": 0.101,
912
+ "train_steps_per_second": 0.002
913
  }
914
  ],
915
  "logging_steps": 2,
916
+ "max_steps": 117,
917
  "num_input_tokens_seen": 0,
918
  "num_train_epochs": 1,
919
  "save_steps": 500,
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d3c54b8da18c9e54b15fbe6df3208ef9f72b48c83ce7d83ada6ae5bfebf9b5ce
3
- size 9656
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f3efb0c43f6345d981a04831c0a4ff2a5b2109e1afc3d3843f248d150f1c8c0
3
+ size 8568