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--- |
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license: apache-2.0 |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1185 |
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- Rouge1: 17.2081 |
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- Rouge2: 8.8374 |
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- Rougel: 16.8033 |
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- Rougelsum: 16.663 |
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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 | 3.9821 | 8.3993 | 2.0894 | 8.1427 | 8.135 | |
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| No log | 2.0 | 606 | 3.3511 | 13.1381 | 5.7193 | 12.8494 | 12.8375 | |
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| No log | 3.0 | 909 | 3.2235 | 15.2502 | 6.5903 | 14.728 | 14.612 | |
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| 5.8943 | 4.0 | 1212 | 3.1695 | 16.1725 | 8.1638 | 15.7655 | 15.6068 | |
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| 5.8943 | 5.0 | 1515 | 3.1579 | 16.3126 | 7.9727 | 15.8308 | 15.7236 | |
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| 5.8943 | 6.0 | 1818 | 3.1346 | 16.8323 | 8.088 | 16.3863 | 16.3343 | |
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| 5.8943 | 7.0 | 2121 | 3.1181 | 16.965 | 8.5799 | 16.6418 | 16.5064 | |
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| 3.7097 | 8.0 | 2424 | 3.1185 | 17.2081 | 8.8374 | 16.8033 | 16.663 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.1 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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