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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: 3.0193 |
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- Rouge1: 17.0688 |
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- Rouge2: 8.3926 |
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- Rougel: 16.8016 |
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- Rougelsum: 16.7103 |
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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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| 3.6768 | 1.0 | 1209 | 3.2182 | 17.8348 | 9.2827 | 17.2983 | 17.2931 | |
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| 3.6447 | 2.0 | 2418 | 3.1029 | 17.459 | 8.8626 | 17.0339 | 16.9027 | |
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| 3.4304 | 3.0 | 3627 | 3.0759 | 15.8089 | 7.6212 | 15.2381 | 15.2037 | |
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| 3.3128 | 4.0 | 4836 | 3.0706 | 16.9995 | 8.7894 | 16.5647 | 16.5779 | |
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| 3.2203 | 5.0 | 6045 | 3.0339 | 16.4001 | 7.7965 | 15.9855 | 15.9288 | |
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| 3.1651 | 6.0 | 7254 | 3.0283 | 16.3259 | 8.0846 | 16.104 | 16.0079 | |
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| 3.1387 | 7.0 | 8463 | 3.0188 | 16.6668 | 8.3136 | 16.374 | 16.3179 | |
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| 3.1139 | 8.0 | 9672 | 3.0193 | 17.0688 | 8.3926 | 16.8016 | 16.7103 | |
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### Framework versions |
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- Transformers 4.46.2 |
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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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