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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: mt5.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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# mt5.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: 1.5093 |
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- Bleu: 38.6464 |
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- Meteor: 0.661 |
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- Chrf++: 60.6878 |
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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: 30000 |
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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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| 4.0484 | 0.3215 | 3000 | 2.1130 | 29.7312 | 0.5872 | 53.2622 | |
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| 2.3309 | 0.6431 | 6000 | 1.8472 | 33.4852 | 0.6209 | 56.6127 | |
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| 2.0987 | 0.9646 | 9000 | 1.7299 | 35.1261 | 0.6355 | 58.0524 | |
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| 1.9355 | 1.2862 | 12000 | 1.6594 | 36.3851 | 0.6449 | 58.9991 | |
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| 1.8568 | 1.6077 | 15000 | 1.5978 | 37.0844 | 0.6499 | 59.4457 | |
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| 1.8039 | 1.9293 | 18000 | 1.5601 | 37.7628 | 0.6562 | 60.145 | |
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| 1.7271 | 2.2508 | 21000 | 1.5298 | 38.1387 | 0.6572 | 60.3042 | |
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| 1.6984 | 2.5723 | 24000 | 1.5148 | 38.5117 | 0.66 | 60.5765 | |
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| 1.6846 | 2.8939 | 27000 | 1.5096 | 38.5563 | 0.6604 | 60.6276 | |
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| 1.6687 | 3.2154 | 30000 | 1.5093 | 38.6464 | 0.661 | 60.6878 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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