outputs
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1438
- Chrf: 0.3504
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: 0.01
- train_batch_size: 4
- eval_batch_size: 8
- seed: 1
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000.0
- training_steps: 20000
Training results
| Training Loss | Epoch | Step | Validation Loss | Chrf |
|---|---|---|---|---|
| 6.5309 | 0.9337 | 2000 | 6.1412 | 0.0 |
| 5.0243 | 1.8674 | 4000 | 4.7869 | 0.0 |
| 5.8503 | 2.8011 | 6000 | 4.6079 | 0.0 |
| 4.8561 | 3.7348 | 8000 | 5.4843 | 0.3906 |
| 5.3422 | 4.6685 | 10000 | 4.6969 | 0.1913 |
| 5.1278 | 5.6022 | 12000 | 4.5267 | 0.0638 |
| 4.7362 | 6.5359 | 14000 | 4.4173 | 0.5746 |
| 4.8027 | 7.4697 | 16000 | 4.2625 | 0.1913 |
| 4.4404 | 8.4034 | 18000 | 4.1877 | 0.1276 |
| 4.3010 | 9.3371 | 20000 | 4.1438 | 0.3504 |
Framework versions
- PEFT 0.19.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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google/mt5-base