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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- summarization |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-amazon-en-es |
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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-small-finetuned-amazon-en-es |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0317 |
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- Rouge1: 16.7841 |
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- Rouge2: 7.5923 |
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- Rougel: 16.3966 |
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- Rougelsum: 16.4835 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 6.5836 | 1.0 | 1209 | 3.3101 | 15.1215 | 5.97 | 14.6831 | 14.7033 | |
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| 3.9149 | 2.0 | 2418 | 3.1711 | 17.272 | 8.5255 | 16.8357 | 16.9754 | |
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| 3.5897 | 3.0 | 3627 | 3.1031 | 17.2062 | 8.8101 | 16.704 | 16.7685 | |
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| 3.4085 | 4.0 | 4836 | 3.0744 | 17.5033 | 8.5182 | 16.977 | 17.1305 | |
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| 3.3123 | 5.0 | 6045 | 3.0542 | 17.5048 | 8.1755 | 16.9628 | 17.0698 | |
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| 3.2467 | 6.0 | 7254 | 3.0375 | 17.1634 | 7.9483 | 16.6977 | 16.8717 | |
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| 3.2043 | 7.0 | 8463 | 3.0282 | 17.1609 | 8.0724 | 16.7818 | 16.9188 | |
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| 3.1836 | 8.0 | 9672 | 3.0317 | 16.7841 | 7.5923 | 16.3966 | 16.4835 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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