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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-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: 3.0882 |
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- Rouge1: 17.4498 |
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- Rouge2: 8.7404 |
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- Rougel: 16.8415 |
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- Rougelsum: 16.9066 |
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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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| 6.4445 | 1.0 | 1209 | 3.3476 | 13.3795 | 5.5143 | 12.8433 | 12.7807 | |
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| 3.9098 | 2.0 | 2418 | 3.2364 | 15.5805 | 7.6998 | 14.9371 | 14.9673 | |
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| 3.5854 | 3.0 | 3627 | 3.1560 | 17.0237 | 8.2938 | 16.3307 | 16.3798 | |
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| 3.4231 | 4.0 | 4836 | 3.1527 | 18.0902 | 9.0059 | 17.1599 | 17.2816 | |
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| 3.3166 | 5.0 | 6045 | 3.1183 | 17.5474 | 8.6267 | 16.9442 | 17.0014 | |
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| 3.2545 | 6.0 | 7254 | 3.0967 | 17.6619 | 8.625 | 17.0709 | 17.0763 | |
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| 3.2021 | 7.0 | 8463 | 3.0897 | 18.1442 | 9.1184 | 17.6043 | 17.5848 | |
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| 3.1818 | 8.0 | 9672 | 3.0882 | 17.4498 | 8.7404 | 16.8415 | 16.9066 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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