1e05_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: 3.9890
- Accuracy: 0.4213
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: 1e-05
- 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 | 5.8378 | 0.2287 |
| No log | 2.0 | 296 | 5.5732 | 0.2491 |
| No log | 3.0 | 444 | 5.3800 | 0.2680 |
| 5.761 | 4.0 | 592 | 5.2259 | 0.2842 |
| 5.761 | 5.0 | 740 | 5.1006 | 0.2963 |
| 5.761 | 6.0 | 888 | 4.9997 | 0.3067 |
| 5.1725 | 7.0 | 1036 | 4.9103 | 0.3153 |
| 5.1725 | 8.0 | 1184 | 4.8287 | 0.3230 |
| 5.1725 | 9.0 | 1332 | 4.7578 | 0.3301 |
| 5.1725 | 10.0 | 1480 | 4.6942 | 0.3376 |
| 4.8482 | 11.0 | 1628 | 4.6364 | 0.3439 |
| 4.8482 | 12.0 | 1776 | 4.5813 | 0.3497 |
| 4.8482 | 13.0 | 1924 | 4.5328 | 0.3554 |
| 4.609 | 14.0 | 2072 | 4.4897 | 0.3610 |
| 4.609 | 15.0 | 2220 | 4.4454 | 0.3657 |
| 4.609 | 16.0 | 2368 | 4.4132 | 0.3702 |
| 4.4241 | 17.0 | 2516 | 4.3742 | 0.3738 |
| 4.4241 | 18.0 | 2664 | 4.3438 | 0.3782 |
| 4.4241 | 19.0 | 2812 | 4.3164 | 0.3817 |
| 4.4241 | 20.0 | 2960 | 4.2879 | 0.3848 |
| 4.283 | 21.0 | 3108 | 4.2602 | 0.3878 |
| 4.283 | 22.0 | 3256 | 4.2373 | 0.3902 |
| 4.283 | 23.0 | 3404 | 4.2160 | 0.3932 |
| 4.1606 | 24.0 | 3552 | 4.1964 | 0.3954 |
| 4.1606 | 25.0 | 3700 | 4.1816 | 0.3976 |
| 4.1606 | 26.0 | 3848 | 4.1605 | 0.3995 |
| 4.1606 | 27.0 | 3996 | 4.1443 | 0.4016 |
| 4.0685 | 28.0 | 4144 | 4.1290 | 0.4034 |
| 4.0685 | 29.0 | 4292 | 4.1146 | 0.4052 |
| 4.0685 | 30.0 | 4440 | 4.1037 | 0.4067 |
| 3.9859 | 31.0 | 4588 | 4.0874 | 0.4082 |
| 3.9859 | 32.0 | 4736 | 4.0784 | 0.4098 |
| 3.9859 | 33.0 | 4884 | 4.0669 | 0.4115 |
| 3.9275 | 34.0 | 5032 | 4.0581 | 0.4125 |
| 3.9275 | 35.0 | 5180 | 4.0479 | 0.4136 |
| 3.9275 | 36.0 | 5328 | 4.0384 | 0.4148 |
| 3.9275 | 37.0 | 5476 | 4.0330 | 0.4159 |
| 3.8799 | 38.0 | 5624 | 4.0262 | 0.4166 |
| 3.8799 | 39.0 | 5772 | 4.0212 | 0.4174 |
| 3.8799 | 40.0 | 5920 | 4.0136 | 0.4180 |
| 3.8348 | 41.0 | 6068 | 4.0111 | 0.4186 |
| 3.8348 | 42.0 | 6216 | 4.0048 | 0.4193 |
| 3.8348 | 43.0 | 6364 | 4.0004 | 0.4195 |
| 3.8151 | 44.0 | 6512 | 3.9978 | 0.4199 |
| 3.8151 | 45.0 | 6660 | 3.9951 | 0.4203 |
| 3.8151 | 46.0 | 6808 | 3.9934 | 0.4207 |
| 3.8151 | 47.0 | 6956 | 3.9904 | 0.4209 |
| 3.7948 | 48.0 | 7104 | 3.9911 | 0.4211 |
| 3.7948 | 49.0 | 7252 | 3.9890 | 0.4213 |
| 3.7948 | 50.0 | 7400 | 3.9890 | 0.4213 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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