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m2m100-T4-es-zap-data
josueu/m2m100-T4-es-zap-data
m2m100-T4-es-zap-data is a machine learning model from josueu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- m2m_100
- Access
- Public
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026
- SHA
- b9081d39
Base models
Model card
From the Hugging Face model README
<!-- 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-T4v1-es-zap-data
This model is a fine-tuned version of facebook/m2m100_418M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4157
- Bleu: 34.7034
- Ter: 51.7157
- Meteor: 0.5754
- Chrf: 58.5004
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Ter | Meteor | Chrf |
|---|---|---|---|---|---|---|---|
| 6.2805 | 1.0 | 161 | 1.8069 | 13.5636 | 71.3235 | 0.4031 | 40.2762 |
| 2.5250 | 2.0 | 322 | 1.4623 | 21.4247 | 62.2549 | 0.4896 | 48.1914 |
| 1.6540 | 3.0 | 483 | 1.2635 | 22.4524 | 60.1716 | 0.4907 | 49.5555 |
| 0.8847 | 4.0 | 644 | 1.2306 | 28.2272 | 56.4951 | 0.5401 | 54.4320 |
| 0.5798 | 5.0 | 805 | 1.2738 | 25.9625 | 59.8039 | 0.5255 | 52.3034 |
| 0.3508 | 6.0 | 966 | 1.2854 | 32.8459 | 54.1667 | 0.5607 | 55.6667 |
| 0.2421 | 7.0 | 1127 | 1.3308 | 31.0852 | 54.0441 | 0.5463 | 55.4113 |
| 0.1745 | 8.0 | 1288 | 1.3297 | 29.9278 | 55.1471 | 0.5511 | 55.7676 |
| 0.1201 | 9.0 | 1449 | 1.3602 | 28.3774 | 56.25 | 0.5435 | 55.0030 |
| 0.0917 | 10.0 | 1610 | 1.3745 | 33.1321 | 51.8382 | 0.5732 | 57.6111 |
| 0.0567 | 11.0 | 1771 | 1.3614 | 33.4271 | 51.7157 | 0.5679 | 57.4082 |
| 0.0320 | 12.0 | 1932 | 1.3889 | 33.0171 | 52.2059 | 0.5655 | 57.8218 |
| 0.0279 | 13.0 | 2093 | 1.4141 | 33.4127 | 52.9412 | 0.5663 | 56.9120 |
| 0.0148 | 14.0 | 2254 | 1.4094 | 34.2420 | 52.4510 | 0.5722 | 57.5340 |
| 0.0132 | 15.0 | 2415 | 1.4157 | 34.7034 | 51.7157 | 0.5754 | 58.5004 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
- Library
- transformers
- Type
- m2m_100
- License
- mit
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026