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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 |
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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 |
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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: 1.1447 |
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- Bleu: 44.0055 |
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- Meteor: 0.6899 |
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- Chrf++: 62.7408 |
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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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| 4.4025 | 0.15 | 2500 | 2.0103 | 27.2729 | 0.5485 | 48.5595 | |
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| 2.4711 | 0.29 | 5000 | 1.7003 | 33.5151 | 0.6064 | 54.1742 | |
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| 2.2228 | 0.44 | 7500 | 1.5685 | 35.7225 | 0.6241 | 56.257 | |
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| 2.0833 | 0.59 | 10000 | 1.4797 | 37.676 | 0.6383 | 57.6397 | |
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| 1.9841 | 0.73 | 12500 | 1.4128 | 38.5011 | 0.6504 | 58.509 | |
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| 1.9135 | 0.88 | 15000 | 1.3693 | 39.7405 | 0.6569 | 59.5371 | |
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| 1.8531 | 1.03 | 17500 | 1.3192 | 40.6354 | 0.6638 | 59.992 | |
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| 1.784 | 1.17 | 20000 | 1.2890 | 41.5264 | 0.6716 | 60.8105 | |
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| 1.7506 | 1.32 | 22500 | 1.2587 | 42.0462 | 0.6737 | 61.1679 | |
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| 1.7214 | 1.47 | 25000 | 1.2359 | 42.1492 | 0.6755 | 61.379 | |
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| 1.698 | 1.61 | 27500 | 1.2125 | 42.5233 | 0.6794 | 61.5581 | |
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| 1.6715 | 1.76 | 30000 | 1.1970 | 42.7034 | 0.6805 | 61.7294 | |
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| 1.6526 | 1.91 | 32500 | 1.1849 | 43.0685 | 0.6834 | 62.0592 | |
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| 1.6257 | 2.05 | 35000 | 1.1699 | 43.2808 | 0.6855 | 62.1626 | |
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| 1.5914 | 2.2 | 37500 | 1.1627 | 43.3637 | 0.685 | 62.2303 | |
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| 1.5818 | 2.35 | 40000 | 1.1545 | 43.6077 | 0.6874 | 62.4906 | |
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| 1.5811 | 2.49 | 42500 | 1.1484 | 43.9335 | 0.6891 | 62.6396 | |
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| 1.5777 | 2.64 | 45000 | 1.1449 | 44.1036 | 0.6903 | 62.8018 | |
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| 1.575 | 2.79 | 47500 | 1.1450 | 43.9408 | 0.6894 | 62.6836 | |
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| 1.5766 | 2.93 | 50000 | 1.1447 | 44.0055 | 0.6899 | 62.7408 | |
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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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