eng_wiki_clm_30
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2540
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 30
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40000
- training_steps: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.1319 | 2000 | 7.5996 |
| 7.6844 | 2.2637 | 4000 | 6.6933 |
| 7.6844 | 3.3956 | 6000 | 6.2852 |
| 6.3411 | 4.5274 | 8000 | 6.0162 |
| 6.3411 | 5.6593 | 10000 | 5.7870 |
| 5.8299 | 6.7912 | 12000 | 5.5636 |
| 5.8299 | 7.9230 | 14000 | 5.3663 |
| 5.4226 | 9.0549 | 16000 | 5.1959 |
| 5.4226 | 10.1868 | 18000 | 5.0538 |
| 5.0963 | 11.3186 | 20000 | 4.9305 |
| 5.0963 | 12.4505 | 22000 | 4.8287 |
| 4.8579 | 13.5823 | 24000 | 4.7431 |
| 4.8579 | 14.7142 | 26000 | 4.6672 |
| 4.673 | 15.8461 | 28000 | 4.6054 |
| 4.673 | 16.9779 | 30000 | 4.5488 |
| 4.5218 | 18.1098 | 32000 | 4.5005 |
| 4.5218 | 19.2417 | 34000 | 4.4625 |
| 4.3942 | 20.3735 | 36000 | 4.4248 |
| 4.3942 | 21.5054 | 38000 | 4.3951 |
| 4.287 | 22.6372 | 40000 | 4.3714 |
| 4.287 | 23.7691 | 42000 | 4.3377 |
| 4.1875 | 24.9010 | 44000 | 4.3180 |
| 4.1875 | 26.0328 | 46000 | 4.3037 |
| 4.088 | 27.1647 | 48000 | 4.2899 |
| 4.088 | 28.2965 | 50000 | 4.2819 |
| 4.0097 | 29.4284 | 52000 | 4.2699 |
| 4.0097 | 30.5603 | 54000 | 4.2628 |
| 3.9437 | 31.6921 | 56000 | 4.2588 |
| 3.9437 | 32.8240 | 58000 | 4.2509 |
| 3.8877 | 33.9559 | 60000 | 4.2439 |
| 3.8877 | 35.0877 | 62000 | 4.2492 |
| 3.8319 | 36.2196 | 64000 | 4.2496 |
| 3.8319 | 37.3514 | 66000 | 4.2485 |
| 3.7878 | 38.4833 | 68000 | 4.2479 |
| 3.7878 | 39.6152 | 70000 | 4.2462 |
| 3.7485 | 40.7470 | 72000 | 4.2456 |
| 3.7485 | 41.8789 | 74000 | 4.2438 |
| 3.7129 | 43.0108 | 76000 | 4.2458 |
| 3.7129 | 44.1426 | 78000 | 4.2496 |
| 3.6752 | 45.2745 | 80000 | 4.2527 |
| 3.6752 | 46.4063 | 82000 | 4.2543 |
| 3.6467 | 47.5382 | 84000 | 4.2530 |
| 3.6467 | 48.6701 | 86000 | 4.2522 |
| 3.6209 | 49.8019 | 88000 | 4.2534 |
| 3.6209 | 50.9338 | 90000 | 4.2521 |
| 3.5947 | 52.0656 | 92000 | 4.2541 |
| 3.5947 | 53.1975 | 94000 | 4.2551 |
| 3.572 | 54.3294 | 96000 | 4.2561 |
| 3.572 | 55.4612 | 98000 | 4.2545 |
| 3.5535 | 56.5931 | 100000 | 4.2540 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1