en_wiki_mlm_42
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2073
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: 42
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.1319 | 2000 | 7.9220 |
| 7.9468 | 2.2637 | 4000 | 7.1138 |
| 7.9468 | 3.3956 | 6000 | 7.0179 |
| 7.0274 | 4.5274 | 8000 | 6.9387 |
| 7.0274 | 5.6593 | 10000 | 6.8684 |
| 6.8824 | 6.7912 | 12000 | 6.8074 |
| 6.8824 | 7.9230 | 14000 | 6.7360 |
| 6.7613 | 9.0549 | 16000 | 6.6897 |
| 6.7613 | 10.1868 | 18000 | 6.6394 |
| 6.6553 | 11.3186 | 20000 | 6.5982 |
| 6.6553 | 12.4505 | 22000 | 6.5549 |
| 6.5571 | 13.5823 | 24000 | 6.4910 |
| 6.5571 | 14.7142 | 26000 | 6.3365 |
| 6.3693 | 15.8461 | 28000 | 6.1672 |
| 6.3693 | 16.9779 | 30000 | 6.0045 |
| 6.0899 | 18.1098 | 32000 | 5.7855 |
| 6.0899 | 19.2417 | 34000 | 5.4393 |
| 5.5439 | 20.3735 | 36000 | 4.9515 |
| 5.5439 | 21.5054 | 38000 | 4.7547 |
| 4.8683 | 22.6372 | 40000 | 4.5845 |
| 4.8683 | 23.7691 | 42000 | 4.4155 |
| 4.5176 | 24.9010 | 44000 | 4.2623 |
| 4.5176 | 26.0328 | 46000 | 4.1626 |
| 4.2542 | 27.1647 | 48000 | 4.0574 |
| 4.2542 | 28.2965 | 50000 | 3.9692 |
| 4.0419 | 29.4284 | 52000 | 3.8587 |
| 4.0419 | 30.5603 | 54000 | 3.7976 |
| 3.886 | 31.6921 | 56000 | 3.7284 |
| 3.886 | 32.8240 | 58000 | 3.6753 |
| 3.7574 | 33.9559 | 60000 | 3.6361 |
| 3.7574 | 35.0877 | 62000 | 3.5934 |
| 3.6518 | 36.2196 | 64000 | 3.5501 |
| 3.6518 | 37.3514 | 66000 | 3.5198 |
| 3.5686 | 38.4833 | 68000 | 3.4513 |
| 3.5686 | 39.6152 | 70000 | 3.4401 |
| 3.4978 | 40.7470 | 72000 | 3.4219 |
| 3.4978 | 41.8789 | 74000 | 3.3757 |
| 3.4364 | 43.0108 | 76000 | 3.3725 |
| 3.4364 | 44.1426 | 78000 | 3.3441 |
| 3.3897 | 45.2745 | 80000 | 3.3154 |
| 3.3897 | 46.4063 | 82000 | 3.3061 |
| 3.3414 | 47.5382 | 84000 | 3.2805 |
| 3.3414 | 48.6701 | 86000 | 3.2789 |
| 3.3082 | 49.8019 | 88000 | 3.2435 |
| 3.3082 | 50.9338 | 90000 | 3.2386 |
| 3.2764 | 52.0656 | 92000 | 3.2367 |
| 3.2764 | 53.1975 | 94000 | 3.2309 |
| 3.261 | 54.3294 | 96000 | 3.2278 |
| 3.261 | 55.4612 | 98000 | 3.2301 |
| 3.2384 | 56.5931 | 100000 | 3.2073 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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