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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: 3.0303 |
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- Rouge1: 16.5661 |
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- Rouge2: 7.6422 |
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- Rougel: 15.9325 |
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- Rougelsum: 16.1062 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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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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| 6.9675 | 1.0 | 1209 | 3.2986 | 15.3957 | 6.8712 | 14.6828 | 14.7531 | |
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| 3.8997 | 2.0 | 2418 | 3.1665 | 16.4337 | 7.643 | 15.6402 | 15.7636 | |
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| 3.5826 | 3.0 | 3627 | 3.1106 | 17.1701 | 8.4324 | 16.2932 | 16.4799 | |
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| 3.421 | 4.0 | 4836 | 3.0963 | 17.3456 | 8.7698 | 16.6576 | 16.7746 | |
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| 3.3089 | 5.0 | 6045 | 3.0490 | 16.7603 | 7.6345 | 16.1315 | 16.163 | |
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| 3.2437 | 6.0 | 7254 | 3.0401 | 16.6348 | 7.9563 | 15.8642 | 16.0271 | |
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| 3.2133 | 7.0 | 8463 | 3.0292 | 16.3252 | 7.6422 | 15.8291 | 15.9831 | |
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| 3.1851 | 8.0 | 9672 | 3.0303 | 16.5661 | 7.6422 | 15.9325 | 16.1062 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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