fr_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: 3.4778
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 | 1.7190 | 2000 | 7.1457 |
| 7.2132 | 3.4379 | 4000 | 5.8791 |
| 7.2132 | 5.1569 | 6000 | 5.4286 |
| 5.4631 | 6.8758 | 8000 | 5.0668 |
| 5.4631 | 8.5948 | 10000 | 4.7749 |
| 4.8227 | 10.3137 | 12000 | 4.5301 |
| 4.8227 | 12.0327 | 14000 | 4.3224 |
| 4.3686 | 13.7516 | 16000 | 4.1502 |
| 4.3686 | 15.4706 | 18000 | 4.0104 |
| 4.0366 | 17.1895 | 20000 | 3.8886 |
| 4.0366 | 18.9085 | 22000 | 3.7868 |
| 3.7884 | 20.6274 | 24000 | 3.7020 |
| 3.7884 | 22.3464 | 26000 | 3.6314 |
| 3.5938 | 24.0653 | 28000 | 3.5711 |
| 3.5938 | 25.7843 | 30000 | 3.5208 |
| 3.4315 | 27.5032 | 32000 | 3.4741 |
| 3.4315 | 29.2222 | 34000 | 3.4476 |
| 3.2967 | 30.9411 | 36000 | 3.4107 |
| 3.2967 | 32.6601 | 38000 | 3.3920 |
| 3.173 | 34.3790 | 40000 | 3.3799 |
| 3.173 | 36.0980 | 42000 | 3.3570 |
| 3.059 | 37.8169 | 44000 | 3.3407 |
| 3.059 | 39.5359 | 46000 | 3.3346 |
| 2.9456 | 41.2548 | 48000 | 3.3449 |
| 2.9456 | 42.9738 | 50000 | 3.3278 |
| 2.8533 | 44.6927 | 52000 | 3.3348 |
| 2.8533 | 46.4117 | 54000 | 3.3441 |
| 2.7722 | 48.1306 | 56000 | 3.3519 |
| 2.7722 | 49.8496 | 58000 | 3.3496 |
| 2.699 | 51.5685 | 60000 | 3.3583 |
| 2.699 | 53.2875 | 62000 | 3.3731 |
| 2.6407 | 55.0064 | 64000 | 3.3695 |
| 2.6407 | 56.7254 | 66000 | 3.3794 |
| 2.5791 | 58.4443 | 68000 | 3.3964 |
| 2.5791 | 60.1882 | 70000 | 3.4037 |
| 2.5335 | 61.9072 | 72000 | 3.3997 |
| 2.5335 | 63.6261 | 74000 | 3.4114 |
| 2.4847 | 65.3451 | 76000 | 3.4238 |
| 2.4847 | 67.0640 | 78000 | 3.4284 |
| 2.4463 | 68.7830 | 80000 | 3.4358 |
| 2.4463 | 70.5019 | 82000 | 3.4461 |
| 2.4082 | 72.2209 | 84000 | 3.4518 |
| 2.4082 | 73.9398 | 86000 | 3.4537 |
| 2.3753 | 75.6588 | 88000 | 3.4625 |
| 2.3753 | 77.3777 | 90000 | 3.4673 |
| 2.346 | 79.0967 | 92000 | 3.4705 |
| 2.346 | 80.8156 | 94000 | 3.4725 |
| 2.3184 | 82.5346 | 96000 | 3.4756 |
| 2.3184 | 84.2535 | 98000 | 3.4784 |
| 2.2992 | 85.9725 | 100000 | 3.4778 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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