reuters-gpt2-text-gen
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.3505
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.8 | 2 | 5.1325 |
| No log | 2.0 | 5 | 4.5158 |
| No log | 2.8 | 7 | 4.3926 |
| 3.2046 | 4.0 | 10 | 4.1889 |
| 3.2046 | 4.8 | 12 | 4.1255 |
| 3.2046 | 6.0 | 15 | 4.0377 |
| 3.2046 | 6.8 | 17 | 4.0633 |
| 2.3854 | 8.0 | 20 | 4.0414 |
| 2.3854 | 8.8 | 22 | 4.0933 |
| 2.3854 | 10.0 | 25 | 4.0976 |
| 2.3854 | 10.8 | 27 | 4.1448 |
| 2.0076 | 12.0 | 30 | 4.2108 |
| 2.0076 | 12.8 | 32 | 4.2002 |
| 2.0076 | 14.0 | 35 | 4.2741 |
| 2.0076 | 14.8 | 37 | 4.2844 |
| 1.7505 | 16.0 | 40 | 4.3736 |
| 1.7505 | 16.8 | 42 | 4.3574 |
| 1.7505 | 18.0 | 45 | 4.4569 |
| 1.7505 | 18.8 | 47 | 4.4581 |
| 1.5509 | 20.0 | 50 | 4.4699 |
| 1.5509 | 20.8 | 52 | 4.5080 |
| 1.5509 | 22.0 | 55 | 4.5407 |
| 1.5509 | 22.8 | 57 | 4.6452 |
| 1.3673 | 24.0 | 60 | 4.5325 |
| 1.3673 | 24.8 | 62 | 4.6152 |
| 1.3673 | 26.0 | 65 | 4.7127 |
| 1.3673 | 26.8 | 67 | 4.6173 |
| 1.2093 | 28.0 | 70 | 4.6912 |
| 1.2093 | 28.8 | 72 | 4.7465 |
| 1.2093 | 30.0 | 75 | 4.7689 |
| 1.2093 | 30.8 | 77 | 4.7705 |
| 1.0458 | 32.0 | 80 | 4.8648 |
| 1.0458 | 32.8 | 82 | 4.9239 |
| 1.0458 | 34.0 | 85 | 4.9503 |
| 1.0458 | 34.8 | 87 | 4.8597 |
| 0.9114 | 36.0 | 90 | 4.9523 |
| 0.9114 | 36.8 | 92 | 4.9581 |
| 0.9114 | 38.0 | 95 | 5.0170 |
| 0.9114 | 38.8 | 97 | 4.9739 |
| 0.7897 | 40.0 | 100 | 4.9779 |
| 0.7897 | 40.8 | 102 | 4.9746 |
| 0.7897 | 42.0 | 105 | 5.1164 |
| 0.7897 | 42.8 | 107 | 5.0466 |
| 0.688 | 44.0 | 110 | 5.1557 |
| 0.688 | 44.8 | 112 | 5.1215 |
| 0.688 | 46.0 | 115 | 5.1176 |
| 0.688 | 46.8 | 117 | 5.1375 |
| 0.6066 | 48.0 | 120 | 5.1657 |
| 0.6066 | 48.8 | 122 | 5.1599 |
| 0.6066 | 50.0 | 125 | 5.1915 |
| 0.6066 | 50.8 | 127 | 5.1978 |
| 0.5272 | 52.0 | 130 | 5.2156 |
| 0.5272 | 52.8 | 132 | 5.2771 |
| 0.5272 | 54.0 | 135 | 5.2110 |
| 0.5272 | 54.8 | 137 | 5.2720 |
| 0.4696 | 56.0 | 140 | 5.2585 |
| 0.4696 | 56.8 | 142 | 5.2798 |
| 0.4696 | 58.0 | 145 | 5.2785 |
| 0.4696 | 58.8 | 147 | 5.2969 |
| 0.424 | 60.0 | 150 | 5.3045 |
| 0.424 | 60.8 | 152 | 5.3076 |
| 0.424 | 62.0 | 155 | 5.3178 |
| 0.424 | 62.8 | 157 | 5.3264 |
| 0.3941 | 64.0 | 160 | 5.3031 |
| 0.3941 | 64.8 | 162 | 5.3250 |
| 0.3941 | 66.0 | 165 | 5.3291 |
| 0.3941 | 66.8 | 167 | 5.3288 |
| 0.3715 | 68.0 | 170 | 5.3393 |
| 0.3715 | 68.8 | 172 | 5.3485 |
| 0.3715 | 70.0 | 175 | 5.3370 |
| 0.3715 | 70.8 | 177 | 5.3340 |
| 0.3608 | 72.0 | 180 | 5.3379 |
| 0.3608 | 72.8 | 182 | 5.3413 |
| 0.3608 | 74.0 | 185 | 5.3434 |
| 0.3608 | 74.8 | 187 | 5.3471 |
| 0.351 | 76.0 | 190 | 5.3487 |
| 0.351 | 76.8 | 192 | 5.3499 |
| 0.351 | 78.0 | 195 | 5.3504 |
| 0.351 | 78.8 | 197 | 5.3505 |
| 0.3516 | 80.0 | 200 | 5.3505 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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