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--- |
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base_model: samzirbo/mT5.en-es.pretrained |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: baseline.europarl |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# baseline.europarl |
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This model is a fine-tuned version of [samzirbo/mT5.en-es.pretrained](https://huggingface.co/samzirbo/mT5.en-es.pretrained) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5556 |
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- Bleu: 28.4134 |
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- Meteor: 0.548 |
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- Chrf++: 50.7588 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 50000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Chrf++ | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:| |
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| 3.7368 | 0.06 | 2500 | 3.7330 | 16.6348 | 0.4263 | 38.9851 | |
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| 1.9501 | 0.11 | 5000 | 3.6988 | 20.5694 | 0.4632 | 42.6268 | |
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| 1.7374 | 0.17 | 7500 | 3.6554 | 21.8374 | 0.4825 | 44.4332 | |
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| 1.6252 | 0.23 | 10000 | 3.6674 | 23.1212 | 0.4954 | 45.8093 | |
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| 1.5421 | 0.28 | 12500 | 3.6407 | 24.144 | 0.5063 | 47.0076 | |
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| 1.4867 | 0.34 | 15000 | 3.6991 | 23.9884 | 0.5055 | 46.9973 | |
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| 1.4413 | 0.39 | 17500 | 3.6669 | 25.0356 | 0.5135 | 47.6982 | |
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| 1.4017 | 0.45 | 20000 | 3.5988 | 25.4766 | 0.5201 | 48.3754 | |
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| 1.3769 | 0.51 | 22500 | 3.6120 | 26.17 | 0.5295 | 49.037 | |
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| 1.3476 | 0.56 | 25000 | 3.6225 | 26.8343 | 0.5341 | 49.5501 | |
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| 1.3252 | 0.62 | 27500 | 3.5913 | 26.7117 | 0.5321 | 49.3981 | |
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| 1.307 | 0.68 | 30000 | 3.6205 | 27.3269 | 0.5385 | 49.9517 | |
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| 1.2926 | 0.73 | 32500 | 3.5624 | 27.7597 | 0.5446 | 50.3568 | |
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| 1.2823 | 0.79 | 35000 | 3.5449 | 27.8457 | 0.5458 | 50.5179 | |
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| 1.2728 | 0.85 | 37500 | 3.5383 | 27.9605 | 0.5444 | 50.3421 | |
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| 1.2663 | 0.9 | 40000 | 3.5556 | 28.1962 | 0.5465 | 50.5512 | |
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| 1.2628 | 0.96 | 42500 | 3.5498 | 28.3077 | 0.5477 | 50.7074 | |
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| 1.2514 | 1.01 | 45000 | 3.5519 | 28.3543 | 0.548 | 50.7669 | |
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| 1.239 | 1.07 | 47500 | 3.5555 | 28.2177 | 0.5473 | 50.6922 | |
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| 1.2357 | 1.13 | 50000 | 3.5556 | 28.4134 | 0.548 | 50.7588 | |
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### Framework versions |
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- Transformers 4.38.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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