5e06_output_dir_clean_df_10-100_noX_100_50_epoch_cluster
This model is a fine-tuned version of nferruz/ProtGPT2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4642
- Accuracy: 0.3637
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 148 | 6.0108 | 0.2185 |
| No log | 2.0 | 296 | 5.8304 | 0.2297 |
| No log | 3.0 | 444 | 5.6868 | 0.2394 |
| 5.9726 | 4.0 | 592 | 5.5732 | 0.2492 |
| 5.9726 | 5.0 | 740 | 5.4748 | 0.2587 |
| 5.9726 | 6.0 | 888 | 5.3871 | 0.2673 |
| 5.5397 | 7.0 | 1036 | 5.3085 | 0.2756 |
| 5.5397 | 8.0 | 1184 | 5.2401 | 0.2827 |
| 5.5397 | 9.0 | 1332 | 5.1811 | 0.2888 |
| 5.5397 | 10.0 | 1480 | 5.1277 | 0.2933 |
| 5.2883 | 11.0 | 1628 | 5.0796 | 0.2983 |
| 5.2883 | 12.0 | 1776 | 5.0358 | 0.3030 |
| 5.2883 | 13.0 | 1924 | 4.9951 | 0.3067 |
| 5.1076 | 14.0 | 2072 | 4.9572 | 0.3103 |
| 5.1076 | 15.0 | 2220 | 4.9200 | 0.3139 |
| 5.1076 | 16.0 | 2368 | 4.8877 | 0.3172 |
| 4.9674 | 17.0 | 2516 | 4.8551 | 0.3203 |
| 4.9674 | 18.0 | 2664 | 4.8258 | 0.3232 |
| 4.9674 | 19.0 | 2812 | 4.8008 | 0.3265 |
| 4.9674 | 20.0 | 2960 | 4.7743 | 0.3289 |
| 4.858 | 21.0 | 3108 | 4.7497 | 0.3317 |
| 4.858 | 22.0 | 3256 | 4.7271 | 0.3338 |
| 4.858 | 23.0 | 3404 | 4.7058 | 0.3363 |
| 4.76 | 24.0 | 3552 | 4.6866 | 0.3384 |
| 4.76 | 25.0 | 3700 | 4.6684 | 0.3404 |
| 4.76 | 26.0 | 3848 | 4.6486 | 0.3425 |
| 4.76 | 27.0 | 3996 | 4.6323 | 0.3443 |
| 4.6863 | 28.0 | 4144 | 4.6155 | 0.3459 |
| 4.6863 | 29.0 | 4292 | 4.6016 | 0.3476 |
| 4.6863 | 30.0 | 4440 | 4.5874 | 0.3490 |
| 4.6168 | 31.0 | 4588 | 4.5742 | 0.3505 |
| 4.6168 | 32.0 | 4736 | 4.5628 | 0.3518 |
| 4.6168 | 33.0 | 4884 | 4.5507 | 0.3534 |
| 4.5684 | 34.0 | 5032 | 4.5412 | 0.3543 |
| 4.5684 | 35.0 | 5180 | 4.5316 | 0.3558 |
| 4.5684 | 36.0 | 5328 | 4.5207 | 0.3570 |
| 4.5684 | 37.0 | 5476 | 4.5132 | 0.3580 |
| 4.5277 | 38.0 | 5624 | 4.5054 | 0.3588 |
| 4.5277 | 39.0 | 5772 | 4.4993 | 0.3597 |
| 4.5277 | 40.0 | 5920 | 4.4931 | 0.3604 |
| 4.4886 | 41.0 | 6068 | 4.4879 | 0.3611 |
| 4.4886 | 42.0 | 6216 | 4.4821 | 0.3617 |
| 4.4886 | 43.0 | 6364 | 4.4778 | 0.3622 |
| 4.4727 | 44.0 | 6512 | 4.4741 | 0.3626 |
| 4.4727 | 45.0 | 6660 | 4.4710 | 0.3630 |
| 4.4727 | 46.0 | 6808 | 4.4691 | 0.3633 |
| 4.4727 | 47.0 | 6956 | 4.4664 | 0.3634 |
| 4.4542 | 48.0 | 7104 | 4.4652 | 0.3636 |
| 4.4542 | 49.0 | 7252 | 4.4644 | 0.3637 |
| 4.4542 | 50.0 | 7400 | 4.4642 | 0.3637 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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