| --- |
| library_name: transformers |
| license: mit |
| base_model: facebook/m2m100_418M |
| tags: |
| - generated_from_trainer |
| metrics: |
| - bleu |
| model-index: |
| - name: m2m100-legal-translation-en-ur |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # m2m100-legal-translation-en-ur |
|
|
| This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2290 |
| - Bleu: 30.9872 |
|
|
| ## 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: 3e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 20 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Bleu | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 8.278 | 0.2688 | 25 | 6.3522 | 3.5831 | |
| | 5.3323 | 0.5376 | 50 | 4.9369 | 9.8940 | |
| | 4.3888 | 0.8065 | 75 | 3.7497 | 12.2129 | |
| | 3.0058 | 1.0753 | 100 | 2.6821 | 15.0216 | |
| | 2.2164 | 1.3441 | 125 | 1.7722 | 16.6899 | |
| | 1.2595 | 1.6129 | 150 | 1.0978 | 18.5312 | |
| | 0.8531 | 1.8817 | 175 | 0.7009 | 19.6160 | |
| | 0.579 | 2.1505 | 200 | 0.4962 | 21.4995 | |
| | 0.4599 | 2.4194 | 225 | 0.4073 | 22.5162 | |
| | 0.3362 | 2.6882 | 250 | 0.3502 | 23.5743 | |
| | 0.353 | 2.9570 | 275 | 0.3122 | 25.6336 | |
| | 0.313 | 3.2258 | 300 | 0.2887 | 27.3754 | |
| | 0.3446 | 3.4946 | 325 | 0.2702 | 28.0800 | |
| | 0.3345 | 3.7634 | 350 | 0.2541 | 29.5058 | |
| | 0.2018 | 4.0323 | 375 | 0.2439 | 30.0331 | |
| | 0.2381 | 4.3011 | 400 | 0.2360 | 30.5859 | |
| | 0.1609 | 4.5699 | 425 | 0.2315 | 30.8617 | |
| | 0.2169 | 4.8387 | 450 | 0.2290 | 30.9872 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.51.1 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.0 |
|
|
