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--- |
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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-reviews-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-reviews-en-es |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0821 |
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- Rouge1: 16.9898 |
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- Rouge2: 8.8591 |
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- Rougel: 16.4898 |
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- Rougelsum: 16.4049 |
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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: 32 |
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- eval_batch_size: 32 |
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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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| No log | 1.0 | 303 | 3.8547 | 8.3494 | 2.0589 | 8.0829 | 8.1616 | |
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| No log | 2.0 | 606 | 3.2801 | 13.8562 | 5.4287 | 13.5685 | 13.5248 | |
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| No log | 3.0 | 909 | 3.1936 | 14.808 | 6.5817 | 14.0409 | 13.997 | |
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| 5.736 | 4.0 | 1212 | 3.1461 | 15.1274 | 7.8439 | 14.7732 | 14.7881 | |
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| 5.736 | 5.0 | 1515 | 3.1016 | 16.5746 | 8.598 | 16.0209 | 15.9155 | |
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| 5.736 | 6.0 | 1818 | 3.0917 | 16.6895 | 8.8052 | 16.1651 | 16.0524 | |
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| 5.736 | 7.0 | 2121 | 3.0836 | 16.9473 | 8.8697 | 16.4392 | 16.3241 | |
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| 3.7032 | 8.0 | 2424 | 3.0821 | 16.9898 | 8.8591 | 16.4898 | 16.4049 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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