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gpt2-alpaca-pandalm

This model is a fine-tuned version of vicgalle/gpt2-alpaca-gpt4 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7704

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
No log 0.0 200 2.3394
No log 0.01 400 2.1772
No log 0.01 600 1.8886
No log 0.01 800 1.5218
No log 0.01 1000 1.2395
No log 0.02 1200 1.1521
No log 0.02 1400 1.0961
No log 0.02 1600 1.0694
No log 0.03 1800 1.0445
No log 0.03 2000 1.0232
No log 0.03 2200 1.0111
No log 0.03 2400 1.0059
No log 0.04 2600 0.9903
No log 0.04 2800 0.9784
1.3639 0.04 3000 0.9913
1.3639 0.04 3200 0.9731
1.3639 0.05 3400 0.9740
1.3639 0.05 3600 0.9744
1.3639 0.05 3800 0.9602
1.3639 0.06 4000 0.9562
1.3639 0.06 4200 0.9550
1.3639 0.06 4400 0.9533
1.3639 0.06 4600 0.9538
1.3639 0.07 4800 0.9422
1.3639 0.07 5000 0.9404
1.3639 0.07 5200 0.9356
1.3639 0.08 5400 0.9295
1.3639 0.08 5600 0.9343
1.3639 0.08 5800 0.9343
0.9303 0.08 6000 0.9281
0.9303 0.09 6200 0.9314
0.9303 0.09 6400 0.9226
0.9303 0.09 6600 0.9187
0.9303 0.09 6800 0.9213
0.9303 0.1 7000 0.9148
0.9303 0.1 7200 0.9122
0.9303 0.1 7400 0.9164
0.9303 0.11 7600 0.9139
0.9303 0.11 7800 0.9114
0.9303 0.11 8000 0.9131
0.9303 0.11 8200 0.9071
0.9303 0.12 8400 0.8997
0.9303 0.12 8600 0.9064
0.9303 0.12 8800 0.9025
0.8876 0.13 9000 0.8972
0.8876 0.13 9200 0.8947
0.8876 0.13 9400 0.8978
0.8876 0.13 9600 0.8989
0.8876 0.14 9800 0.8938
0.8876 0.14 10000 0.8935
0.8876 0.14 10200 0.8891
0.8876 0.15 10400 0.8950
0.8876 0.15 10600 0.8893
0.8876 0.15 10800 0.8845
0.8876 0.15 11000 0.8883
0.8876 0.16 11200 0.8925
0.8876 0.16 11400 0.8842
0.8876 0.16 11600 0.8828
0.8876 0.16 11800 0.8822
0.8668 0.17 12000 0.8815
0.8668 0.17 12200 0.8823
0.8668 0.17 12400 0.8821
0.8668 0.18 12600 0.8830
0.8668 0.18 12800 0.8742
0.8668 0.18 13000 0.8750
0.8668 0.18 13200 0.8738
0.8668 0.19 13400 0.8780
0.8668 0.19 13600 0.8746
0.8668 0.19 13800 0.8775
0.8668 0.2 14000 0.8755
0.8668 0.2 14200 0.8715
0.8668 0.2 14400 0.8730
0.8668 0.2 14600 0.8697
0.8668 0.21 14800 0.8647
0.853 0.21 15000 0.8639
0.853 0.21 15200 0.8612
0.853 0.21 15400 0.8580
0.853 0.22 15600 0.8613
0.853 0.22 15800 0.8605
0.853 0.22 16000 0.8619
0.853 0.23 16200 0.8608
0.853 0.23 16400 0.8607
0.853 0.23 16600 0.8597
0.853 0.23 16800 0.8553
0.853 0.24 17000 0.8575
0.853 0.24 17200 0.8537
0.853 0.24 17400 0.8525
0.853 0.25 17600 0.8529
0.853 0.25 17800 0.8552
0.8444 0.25 18000 0.8546
0.8444 0.25 18200 0.8541
0.8444 0.26 18400 0.8568
0.8444 0.26 18600 0.8563
0.8444 0.26 18800 0.8536
0.8444 0.26 19000 0.8496
0.8444 0.27 19200 0.8562
0.8444 0.27 19400 0.8522
0.8444 0.27 19600 0.8560
0.8444 0.28 19800 0.8512
0.8444 0.28 20000 0.8485
0.8444 0.28 20200 0.8527
0.8444 0.28 20400 0.8491
0.8444 0.29 20600 0.8482
0.8444 0.29 20800 0.8511
0.8377 0.29 21000 0.8504
0.8377 0.3 21200 0.8480
0.8377 0.3 21400 0.8463
0.8377 0.3 21600 0.8484
0.8377 0.3 21800 0.8464
0.8377 0.31 22000 0.8489
0.8377 0.31 22200 0.8478
0.8377 0.31 22400 0.8481
0.8377 0.32 22600 0.8461
0.8377 0.32 22800 0.8434
0.8377 0.32 23000 0.8430
0.8377 0.32 23200 0.8473
0.8377 0.33 23400 0.8401
0.8377 0.33 23600 0.8434
0.8377 0.33 23800 0.8463
0.8319 0.33 24000 0.8454
0.8319 0.34 24200 0.8430
0.8319 0.34 24400 0.8448
0.8319 0.34 24600 0.8432
0.8319 0.35 24800 0.8461
0.8319 0.35 25000 0.8397
0.8319 0.35 25200 0.8426
0.8319 0.35 25400 0.8421
0.8319 0.36 25600 0.8396
0.8319 0.36 25800 0.8392
0.8319 0.36 26000 0.8427
0.8319 0.37 26200 0.8421
0.8319 0.37 26400 0.8438
0.8319 0.37 26600 0.8412
0.8319 0.37 26800 0.8383
0.8276 0.38 27000 0.8378
0.8276 0.38 27200 0.8374
0.8276 0.38 27400 0.8392
0.8276 0.38 27600 0.8376
0.8276 0.39 27800 0.8340
0.8276 0.39 28000 0.8375
0.8276 0.39 28200 0.8389
0.8276 0.4 28400 0.8359
0.8276 0.4 28600 0.8354
0.8276 0.4 28800 0.8351
0.8276 0.4 29000 0.8354
0.8276 0.41 29200 0.8348
0.8276 0.41 29400 0.8384
0.8276 0.41 29600 0.8354
0.8276 0.42 29800 0.8343
0.8182 0.42 30000 0.8333
0.8182 0.42 30200 0.8372
0.8182 0.42 30400 0.8337
0.8182 0.43 30600 0.8320
0.8182 0.43 30800 0.8338
0.8182 0.43 31000 0.8318
0.8182 0.44 31200 0.8326
0.8182 0.44 31400 0.8309
0.8182 0.44 31600 0.8310
0.8182 0.44 31800 0.8319
0.8182 0.45 32000 0.8331
0.8182 0.45 32200 0.8338
0.8182 0.45 32400 0.8301
0.8182 0.45 32600 0.8282
0.8182 0.46 32800 0.8270
0.8161 0.46 33000 0.8229
0.8161 0.46 33200 0.8258
0.8161 0.47 33400 0.8275
0.8161 0.47 33600 0.8285
0.8161 0.47 33800 0.8232
0.8161 0.47 34000 0.8272
0.8161 0.48 34200 0.8236
0.8161 0.48 34400 0.8228
0.8161 0.48 34600 0.8217
0.8161 0.49 34800 0.8212
0.8161 0.49 35000 0.8205
0.8161 0.49 35200 0.8211
0.8161 0.49 35400 0.8278
0.8161 0.5 35600 0.8277
0.8161 0.5 35800 0.8250
0.8139 0.5 36000 0.8255
0.8139 0.5 36200 0.8253
0.8139 0.51 36400 0.8253
0.8139 0.51 36600 0.8243
0.8139 0.51 36800 0.8254
0.8139 0.52 37000 0.8241
0.8139 0.52 37200 0.8250
0.8139 0.52 37400 0.8236
0.8139 0.52 37600 0.8250
0.8139 0.53 37800 0.8227
0.8139 0.53 38000 0.8230
0.8139 0.53 38200 0.8268
0.8139 0.54 38400 0.8233
0.8139 0.54 38600 0.8224
0.8139 0.54 38800 0.8214
0.8089 0.54 39000 0.8266
0.8089 0.55 39200 0.8221
0.8089 0.55 39400 0.8223
0.8089 0.55 39600 0.8196
0.8089 0.55 39800 0.8189
0.8089 0.56 40000 0.8228
0.8089 0.56 40200 0.8174
0.8089 0.56 40400 0.8239
0.8089 0.57 40600 0.8209
0.8089 0.57 40800 0.8213
0.8089 0.57 41000 0.8202
0.8089 0.57 41200 0.8225
0.8089 0.58 41400 0.8214
0.8089 0.58 41600 0.8204
0.8089 0.58 41800 0.8197
0.8056 0.59 42000 0.8191
0.8056 0.59 42200 0.8214
0.8056 0.59 42400 0.8128
0.8056 0.59 42600 0.8160
0.8056 0.6 42800 0.8182
0.8056 0.6 43000 0.8191
0.8056 0.6 43200 0.8154
0.8056 0.61 43400 0.8173
0.8056 0.61 43600 0.8126
0.8056 0.61 43800 0.8130
0.8056 0.61 44000 0.8154
0.8056 0.62 44200 0.8141
0.8056 0.62 44400 0.8170
0.8056 0.62 44600 0.8137
0.8056 0.62 44800 0.8189
0.805 0.63 45000 0.8162
0.805 0.63 45200 0.8133
0.805 0.63 45400 0.8166
0.805 0.64 45600 0.8164
0.805 0.64 45800 0.8130
0.805 0.64 46000 0.8118
0.805 0.64 46200 0.8157
0.805 0.65 46400 0.8145
0.805 0.65 46600 0.8128
0.805 0.65 46800 0.8107
0.805 0.66 47000 0.8144
0.805 0.66 47200 0.8143
0.805 0.66 47400 0.8161
0.805 0.66 47600 0.8141
0.805 0.67 47800 0.8162
0.8006 0.67 48000 0.8118
0.8006 0.67 48200 0.8174
0.8006 0.67 48400 0.8156
0.8006 0.68 48600 0.8131
0.8006 0.68 48800 0.8119
0.8006 0.68 49000 0.8083
0.8006 0.69 49200 0.8083
0.8006 0.69 49400 0.8126
0.8006 0.69 49600 0.8134
0.8006 0.69 49800 0.8151
0.8006 0.7 50000 0.8165
0.8006 0.7 50200 0.8164
0.8006 0.7 50400 0.8148
0.8006 0.71 50600 0.8091
0.8006 0.71 50800 0.8135
0.7982 0.71 51000 0.8146
0.7982 0.71 51200 0.8126
0.7982 0.72 51400 0.8119
0.7982 0.72 51600 0.8108
0.7982 0.72 51800 0.8125
0.7982 0.73 52000 0.8125
0.7982 0.73 52200 0.8123
0.7982 0.73 52400 0.8101
0.7982 0.73 52600 0.8093
0.7982 0.74 52800 0.8086
0.7982 0.74 53000 0.8083
0.7982 0.74 53200 0.8093
0.7982 0.74 53400 0.8090
0.7982 0.75 53600 0.8083
0.7982 0.75 53800 0.8115
0.794 0.75 54000 0.8092
0.794 0.76 54200 0.8077
0.794 0.76 54400 0.8076
0.794 0.76 54600 0.8081
0.794 0.76 54800 0.8105
0.794 0.77 55000 0.8093
0.794 0.77 55200 0.8108
0.794 0.77 55400 0.8104
0.794 0.78 55600 0.8051
0.794 0.78 55800 0.8083
0.794 0.78 56000 0.8073
0.794 0.78 56200 0.8107
0.794 0.79 56400 0.8072
0.794 0.79 56600 0.8050
0.794 0.79 56800 0.8043
0.7913 0.79 57000 0.8050
0.7913 0.8 57200 0.8054
0.7913 0.8 57400 0.8087
0.7913 0.8 57600 0.8088
0.7913 0.81 57800 0.8074
0.7913 0.81 58000 0.8081
0.7913 0.81 58200 0.8077
0.7913 0.81 58400 0.8058
0.7913 0.82 58600 0.8031
0.7913 0.82 58800 0.8016
0.7913 0.82 59000 0.8029
0.7913 0.83 59200 0.8063
0.7913 0.83 59400 0.8048
0.7913 0.83 59600 0.8059
0.7913 0.83 59800 0.8043
0.7921 0.84 60000 0.8013
0.7921 0.84 60200 0.8017
0.7921 0.84 60400 0.8054
0.7921 0.85 60600 0.8068
0.7921 0.85 60800 0.8084
0.7921 0.85 61000 0.8076
0.7921 0.85 61200 0.8034
0.7921 0.86 61400 0.8020
0.7921 0.86 61600 0.8058
0.7921 0.86 61800 0.8073
0.7921 0.86 62000 0.8042
0.7921 0.87 62200 0.8023
0.7921 0.87 62400 0.8029
0.7921 0.87 62600 0.8032
0.7921 0.88 62800 0.8034
0.785 0.88 63000 0.8032
0.785 0.88 63200 0.8033
0.785 0.88 63400 0.8038
0.785 0.89 63600 0.8013
0.785 0.89 63800 0.8028
0.785 0.89 64000 0.7991
0.785 0.9 64200 0.8013
0.785 0.9 64400 0.8042
0.785 0.9 64600 0.8053
0.785 0.9 64800 0.8044
0.785 0.91 65000 0.8019
0.785 0.91 65200 0.8041
0.785 0.91 65400 0.8032
0.785 0.91 65600 0.8031
0.785 0.92 65800 0.8062
0.7854 0.92 66000 0.8023
0.7854 0.92 66200 0.8035
0.7854 0.93 66400 0.8018
0.7854 0.93 66600 0.7983
0.7854 0.93 66800 0.7997
0.7854 0.93 67000 0.8021
0.7854 0.94 67200 0.8012
0.7854 0.94 67400 0.8019
0.7854 0.94 67600 0.7994
0.7854 0.95 67800 0.7990
0.7854 0.95 68000 0.7978
0.7854 0.95 68200 0.8005
0.7854 0.95 68400 0.7997
0.7854 0.96 68600 0.7971
0.7854 0.96 68800 0.8005
0.7826 0.96 69000 0.7952
0.7826 0.96 69200 0.7946
0.7826 0.97 69400 0.7963
0.7826 0.97 69600 0.7953
0.7826 0.97 69800 0.7996
0.7826 0.98 70000 0.7983
0.7826 0.98 70200 0.7998
0.7826 0.98 70400 0.8009
0.7826 0.98 70600 0.8022
0.7826 0.99 70800 0.8012
0.7826 0.99 71000 0.8000
0.7826 0.99 71200 0.7997
0.7826 1.0 71400 0.7999
0.7826 1.0 71600 0.7989
0.7826 1.0 71800 0.7960
0.7808 1.0 72000 0.7980
0.7808 1.01 72200 0.7973
0.7808 1.01 72400 0.7966
0.7808 1.01 72600 0.7977
0.7808 1.02 72800 0.7949
0.7808 1.02 73000 0.7980
0.7808 1.02 73200 0.7947
0.7808 1.02 73400 0.8017
0.7808 1.03 73600 0.7994
0.7808 1.03 73800 0.7972
0.7808 1.03 74000 0.7937
0.7808 1.03 74200 0.7924
0.7808 1.04 74400 0.7942
0.7808 1.04 74600 0.7946
0.7808 1.04 74800 0.7958
0.7802 1.05 75000 0.7957
0.7802 1.05 75200 0.7946
0.7802 1.05 75400 0.7964
0.7802 1.05 75600 0.7934
0.7802 1.06 75800 0.7965
0.7802 1.06 76000 0.7960
0.7802 1.06 76200 0.7969
0.7802 1.07 76400 0.7980
0.7802 1.07 76600 0.7948
0.7802 1.07 76800 0.7976
0.7802 1.07 77000 0.7957
0.7802 1.08 77200 0.7988
0.7802 1.08 77400 0.7954
0.7802 1.08 77600 0.7974
0.7802 1.08 77800 0.7987
0.7762 1.09 78000 0.8014
0.7762 1.09 78200 0.7959
0.7762 1.09 78400 0.7972
0.7762 1.1 78600 0.7972
0.7762 1.1 78800 0.7956
0.7762 1.1 79000 0.7959
0.7762 1.1 79200 0.7934
0.7762 1.11 79400 0.7969
0.7762 1.11 79600 0.7955
0.7762 1.11 79800 0.7935
0.7762 1.12 80000 0.7946
0.7762 1.12 80200 0.7945
0.7762 1.12 80400 0.7914
0.7762 1.12 80600 0.7912
0.7762 1.13 80800 0.7910
0.7796 1.13 81000 0.7923
0.7796 1.13 81200 0.7924
0.7796 1.14 81400 0.7916
0.7796 1.14 81600 0.7913
0.7796 1.14 81800 0.7939
0.7796 1.14 82000 0.7953
0.7796 1.15 82200 0.7920
0.7796 1.15 82400 0.7925
0.7796 1.15 82600 0.7910
0.7796 1.15 82800 0.7930
0.7796 1.16 83000 0.7911
0.7796 1.16 83200 0.7922
0.7796 1.16 83400 0.7939
0.7796 1.17 83600 0.7931
0.7796 1.17 83800 0.7928
0.7733 1.17 84000 0.7923
0.7733 1.17 84200 0.7906
0.7733 1.18 84400 0.7911
0.7733 1.18 84600 0.7910
0.7733 1.18 84800 0.7922
0.7733 1.19 85000 0.7907
0.7733 1.19 85200 0.7913
0.7733 1.19 85400 0.7904
0.7733 1.19 85600 0.7906
0.7733 1.2 85800 0.7905
0.7733 1.2 86000 0.7867
0.7733 1.2 86200 0.7871
0.7733 1.2 86400 0.7881
0.7733 1.21 86600 0.7916
0.7733 1.21 86800 0.7927
0.7675 1.21 87000 0.7916
0.7675 1.22 87200 0.7907
0.7675 1.22 87400 0.7905
0.7675 1.22 87600 0.7915
0.7675 1.22 87800 0.7902
0.7675 1.23 88000 0.7880
0.7675 1.23 88200 0.7864
0.7675 1.23 88400 0.7864
0.7675 1.24 88600 0.7887
0.7675 1.24 88800 0.7892
0.7675 1.24 89000 0.7889
0.7675 1.24 89200 0.7892
0.7675 1.25 89400 0.7873
0.7675 1.25 89600 0.7888
0.7675 1.25 89800 0.7874
0.7711 1.25 90000 0.7914
0.7711 1.26 90200 0.7899
0.7711 1.26 90400 0.7885
0.7711 1.26 90600 0.7872
0.7711 1.27 90800 0.7868
0.7711 1.27 91000 0.7862
0.7711 1.27 91200 0.7849
0.7711 1.27 91400 0.7875
0.7711 1.28 91600 0.7877
0.7711 1.28 91800 0.7902
0.7711 1.28 92000 0.7907
0.7711 1.29 92200 0.7897
0.7711 1.29 92400 0.7892
0.7711 1.29 92600 0.7827
0.7711 1.29 92800 0.7872
0.7669 1.3 93000 0.7869
0.7669 1.3 93200 0.7847
0.7669 1.3 93400 0.7867
0.7669 1.31 93600 0.7852
0.7669 1.31 93800 0.7885
0.7669 1.31 94000 0.7893
0.7669 1.31 94200 0.7884
0.7669 1.32 94400 0.7865
0.7669 1.32 94600 0.7870
0.7669 1.32 94800 0.7907
0.7669 1.32 95000 0.7867
0.7669 1.33 95200 0.7891
0.7669 1.33 95400 0.7886
0.7669 1.33 95600 0.7879
0.7669 1.34 95800 0.7879
0.7695 1.34 96000 0.7894
0.7695 1.34 96200 0.7875
0.7695 1.34 96400 0.7853
0.7695 1.35 96600 0.7866
0.7695 1.35 96800 0.7856
0.7695 1.35 97000 0.7846
0.7695 1.36 97200 0.7852
0.7695 1.36 97400 0.7855
0.7695 1.36 97600 0.7860
0.7695 1.36 97800 0.7869
0.7695 1.37 98000 0.7859
0.7695 1.37 98200 0.7842
0.7695 1.37 98400 0.7882
0.7695 1.37 98600 0.7886
0.7695 1.38 98800 0.7868
0.7659 1.38 99000 0.7871
0.7659 1.38 99200 0.7870
0.7659 1.39 99400 0.7850
0.7659 1.39 99600 0.7868
0.7659 1.39 99800 0.7863
0.7659 1.39 100000 0.7864
0.7659 1.4 100200 0.7880
0.7659 1.4 100400 0.7865
0.7659 1.4 100600 0.7863
0.7659 1.41 100800 0.7865
0.7659 1.41 101000 0.7875
0.7659 1.41 101200 0.7890
0.7659 1.41 101400 0.7888
0.7659 1.42 101600 0.7885
0.7659 1.42 101800 0.7870
0.7663 1.42 102000 0.7853
0.7663 1.43 102200 0.7887
0.7663 1.43 102400 0.7857
0.7663 1.43 102600 0.7880
0.7663 1.43 102800 0.7860
0.7663 1.44 103000 0.7871
0.7663 1.44 103200 0.7865
0.7663 1.44 103400 0.7867
0.7663 1.44 103600 0.7859
0.7663 1.45 103800 0.7881
0.7663 1.45 104000 0.7866
0.7663 1.45 104200 0.7871
0.7663 1.46 104400 0.7862
0.7663 1.46 104600 0.7867
0.7663 1.46 104800 0.7857
0.7678 1.46 105000 0.7876
0.7678 1.47 105200 0.7906
0.7678 1.47 105400 0.7861
0.7678 1.47 105600 0.7881
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0.7474 2.96 212400 0.7704
0.7474 2.96 212600 0.7704
0.7474 2.97 212800 0.7704
0.7469 2.97 213000 0.7704
0.7469 2.97 213200 0.7704
0.7469 2.98 213400 0.7704
0.7469 2.98 213600 0.7704
0.7469 2.98 213800 0.7704
0.7469 2.98 214000 0.7704
0.7469 2.99 214200 0.7704
0.7469 2.99 214400 0.7704
0.7469 2.99 214600 0.7704
0.7469 3.0 214800 0.7704
0.7469 3.0 215000 0.7704

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.1.2
  • Datasets 2.19.0
  • Tokenizers 0.13.3
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