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gpt2_finetuned_wolfram
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.2595
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 113 | 6.3789 |
| No log | 2.0 | 226 | 6.0746 |
| No log | 3.0 | 339 | 5.7649 |
| No log | 4.0 | 452 | 5.4453 |
| 5.9875 | 5.0 | 565 | 5.2142 |
| 5.9875 | 6.0 | 678 | 5.0967 |
| 5.9875 | 7.0 | 791 | 5.0143 |
| 5.9875 | 8.0 | 904 | 4.9429 |
| 4.5754 | 9.0 | 1017 | 4.8936 |
| 4.5754 | 10.0 | 1130 | 4.8722 |
| 4.5754 | 11.0 | 1243 | 4.8700 |
| 4.5754 | 12.0 | 1356 | 4.8362 |
| 4.5754 | 13.0 | 1469 | 4.8246 |
| 4.0366 | 14.0 | 1582 | 4.8242 |
| 4.0366 | 15.0 | 1695 | 4.8149 |
| 4.0366 | 16.0 | 1808 | 4.8062 |
| 4.0366 | 17.0 | 1921 | 4.8065 |
| 3.8118 | 18.0 | 2034 | 4.8288 |
| 3.8118 | 19.0 | 2147 | 4.8035 |
| 3.8118 | 20.0 | 2260 | 4.8009 |
| 3.8118 | 21.0 | 2373 | 4.7835 |
| 3.8118 | 22.0 | 2486 | 4.7865 |
| 3.6394 | 23.0 | 2599 | 4.7833 |
| 3.6394 | 24.0 | 2712 | 4.7776 |
| 3.6394 | 25.0 | 2825 | 4.8030 |
| 3.6394 | 26.0 | 2938 | 4.7684 |
| 3.5105 | 27.0 | 3051 | 4.7724 |
| 3.5105 | 28.0 | 3164 | 4.7803 |
| 3.5105 | 29.0 | 3277 | 4.7792 |
| 3.5105 | 30.0 | 3390 | 4.8027 |
| 3.38 | 31.0 | 3503 | 4.8000 |
| 3.38 | 32.0 | 3616 | 4.8046 |
| 3.38 | 33.0 | 3729 | 4.7751 |
| 3.38 | 34.0 | 3842 | 4.7774 |
| 3.38 | 35.0 | 3955 | 4.7733 |
| 3.2382 | 36.0 | 4068 | 4.7886 |
| 3.2382 | 37.0 | 4181 | 4.7892 |
| 3.2382 | 38.0 | 4294 | 4.7876 |
| 3.2382 | 39.0 | 4407 | 4.7965 |
| 3.1022 | 40.0 | 4520 | 4.7879 |
| 3.1022 | 41.0 | 4633 | 4.7829 |
| 3.1022 | 42.0 | 4746 | 4.7884 |
| 3.1022 | 43.0 | 4859 | 4.7845 |
| 3.1022 | 44.0 | 4972 | 4.8193 |
| 2.9571 | 45.0 | 5085 | 4.7947 |
| 2.9571 | 46.0 | 5198 | 4.7968 |
| 2.9571 | 47.0 | 5311 | 4.7894 |
| 2.9571 | 48.0 | 5424 | 4.7892 |
| 2.7555 | 49.0 | 5537 | 4.7914 |
| 2.7555 | 50.0 | 5650 | 4.8099 |
| 2.7555 | 51.0 | 5763 | 4.8029 |
| 2.7555 | 52.0 | 5876 | 4.8000 |
| 2.7555 | 53.0 | 5989 | 4.8092 |
| 2.5656 | 54.0 | 6102 | 4.8111 |
| 2.5656 | 55.0 | 6215 | 4.8257 |
| 2.5656 | 56.0 | 6328 | 4.8109 |
| 2.5656 | 57.0 | 6441 | 4.8457 |
| 2.3501 | 58.0 | 6554 | 4.8428 |
| 2.3501 | 59.0 | 6667 | 4.8519 |
| 2.3501 | 60.0 | 6780 | 4.8652 |
| 2.3501 | 61.0 | 6893 | 4.8788 |
| 2.141 | 62.0 | 7006 | 4.8910 |
| 2.141 | 63.0 | 7119 | 4.8928 |
| 2.141 | 64.0 | 7232 | 4.9112 |
| 2.141 | 65.0 | 7345 | 4.9219 |
| 2.141 | 66.0 | 7458 | 4.9403 |
| 1.9122 | 67.0 | 7571 | 4.9585 |
| 1.9122 | 68.0 | 7684 | 4.9726 |
| 1.9122 | 69.0 | 7797 | 4.9904 |
| 1.9122 | 70.0 | 7910 | 5.0118 |
| 1.7176 | 71.0 | 8023 | 5.0129 |
| 1.7176 | 72.0 | 8136 | 5.0303 |
| 1.7176 | 73.0 | 8249 | 5.0529 |
| 1.7176 | 74.0 | 8362 | 5.0610 |
| 1.7176 | 75.0 | 8475 | 5.0821 |
| 1.5292 | 76.0 | 8588 | 5.0931 |
| 1.5292 | 77.0 | 8701 | 5.1154 |
| 1.5292 | 78.0 | 8814 | 5.1319 |
| 1.5292 | 79.0 | 8927 | 5.1394 |
| 1.3843 | 80.0 | 9040 | 5.1529 |
| 1.3843 | 81.0 | 9153 | 5.1711 |
| 1.3843 | 82.0 | 9266 | 5.1802 |
| 1.3843 | 83.0 | 9379 | 5.1952 |
| 1.3843 | 84.0 | 9492 | 5.2088 |
| 1.2643 | 85.0 | 9605 | 5.2170 |
| 1.2643 | 86.0 | 9718 | 5.2160 |
| 1.2643 | 87.0 | 9831 | 5.2267 |
| 1.2643 | 88.0 | 9944 | 5.2346 |
| 1.1928 | 89.0 | 10057 | 5.2418 |
| 1.1928 | 90.0 | 10170 | 5.2463 |
| 1.1928 | 91.0 | 10283 | 5.2505 |
| 1.1928 | 92.0 | 10396 | 5.2522 |
| 1.1556 | 93.0 | 10509 | 5.2538 |
| 1.1556 | 94.0 | 10622 | 5.2557 |
| 1.1556 | 95.0 | 10735 | 5.2566 |
| 1.1556 | 96.0 | 10848 | 5.2585 |
| 1.1556 | 97.0 | 10961 | 5.2594 |
| 1.1268 | 98.0 | 11074 | 5.2596 |
| 1.1268 | 99.0 | 11187 | 5.2595 |
| 1.1268 | 100.0 | 11300 | 5.2595 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
