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mbart50-es-zapv3
josueu/mbart50-es-zapv3
mbart50-es-zapv3 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
- mbart
- Access
- Public
- Created
- Apr 10, 2026
- Updated
- Apr 11, 2026
- SHA
- 632c2b67
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. -->
mbart50-es-zapv3
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2895
- Bleu: 23.2680
- Ter: 62.9771
- Meteor: 0.5012
- Chrf: 49.1953
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Ter | Meteor | Chrf |
|---|---|---|---|---|---|---|---|
| 6.1208 | 1.0 | 179 | 0.4628 | 7.8281 | 84.4466 | 0.2642 | 30.7944 |
| 0.7001 | 2.0 | 358 | 0.6760 | 0.0 | 100.0 | 0.0 | 0.0074 |
| 0.2437 | 3.0 | 537 | 0.2388 | 16.4870 | 72.8053 | 0.3896 | 40.2706 |
| 0.1298 | 4.0 | 716 | 0.2254 | 19.4490 | 70.2290 | 0.4335 | 44.2058 |
| 0.0853 | 5.0 | 895 | 0.2333 | 18.8371 | 66.0305 | 0.4509 | 44.7725 |
| 0.0722 | 6.0 | 1074 | 0.2472 | 23.2294 | 63.8359 | 0.4851 | 47.3178 |
| 0.0389 | 7.0 | 1253 | 0.2645 | 21.4190 | 64.5038 | 0.4614 | 46.9929 |
| 0.0404 | 8.0 | 1432 | 0.2661 | 20.9712 | 64.9809 | 0.4664 | 47.0832 |
| 0.0299 | 9.0 | 1611 | 0.2761 | 22.9324 | 64.4084 | 0.4989 | 49.5780 |
| 0.0239 | 10.0 | 1790 | 0.2821 | 22.7716 | 62.7863 | 0.4986 | 49.8536 |
| 0.0261 | 11.0 | 1969 | 0.2808 | 24.7373 | 60.3053 | 0.5092 | 50.6788 |
| 0.0165 | 12.0 | 2148 | 0.2866 | 22.7118 | 60.3053 | 0.5112 | 50.6475 |
| 0.0175 | 13.0 | 2327 | 0.3255 | 19.5063 | 64.4084 | 0.4480 | 46.9423 |
| 0.0161 | 14.0 | 2506 | 0.2953 | 24.3036 | 60.8779 | 0.5021 | 50.7556 |
| 0.0150 | 15.0 | 2685 | 0.2917 | 25.2649 | 60.6870 | 0.5010 | 49.9172 |
| 0.0193 | 16.0 | 2864 | 0.2876 | 22.9039 | 59.7328 | 0.5004 | 50.0787 |
| 0.0315 | 17.0 | 3043 | 0.2895 | 23.2680 | 62.9771 | 0.5012 | 49.1953 |
Framework versions
- Transformers 5.5.3
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
- Library
- transformers
- Type
- mbart
- License
- mit
- Created
- Apr 10, 2026
- Updated
- Apr 11, 2026