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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: 3.0132 |
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- Rouge1: 16.4719 |
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- Rouge2: 7.9366 |
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- Rougel: 16.2123 |
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- Rougelsum: 16.2853 |
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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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- distributed_type: multi-GPU |
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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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| 3.9249 | 1.0 | 1209 | 3.1904 | 15.8207 | 8.0555 | 15.4584 | 15.648 | |
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| 3.5688 | 2.0 | 2418 | 3.0812 | 16.3271 | 8.1479 | 15.9001 | 16.0134 | |
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| 3.3905 | 3.0 | 3627 | 3.0442 | 15.9864 | 7.295 | 15.4247 | 15.5848 | |
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| 3.2728 | 4.0 | 4836 | 3.0304 | 16.2893 | 7.5851 | 15.9494 | 16.0117 | |
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| 3.1958 | 5.0 | 6045 | 3.0169 | 15.4888 | 7.4495 | 15.2244 | 15.2326 | |
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| 3.1359 | 6.0 | 7254 | 3.0158 | 16.3866 | 8.2218 | 16.0625 | 16.0953 | |
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| 3.1059 | 7.0 | 8463 | 3.0075 | 15.9134 | 7.8387 | 15.626 | 15.6499 | |
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| 3.0852 | 8.0 | 9672 | 3.0132 | 16.4719 | 7.9366 | 16.2123 | 16.2853 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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