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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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base_model: google/mt5-small |
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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: 3.0393 |
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- Rouge1: 17.3313 |
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- Rouge2: 8.1251 |
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- Rougel: 17.0359 |
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- Rougelsum: 16.9503 |
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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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| 6.6665 | 1.0 | 1209 | 3.2917 | 13.908 | 5.5316 | 13.4368 | 13.4302 | |
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| 3.8961 | 2.0 | 2418 | 3.1711 | 16.247 | 8.7234 | 15.7703 | 15.6964 | |
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| 3.5801 | 3.0 | 3627 | 3.0917 | 17.3455 | 8.2467 | 16.8631 | 16.8147 | |
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| 3.4258 | 4.0 | 4836 | 3.0583 | 16.0978 | 7.83 | 15.8065 | 15.7725 | |
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| 3.3154 | 5.0 | 6045 | 3.0573 | 17.5531 | 8.7811 | 17.2252 | 17.2055 | |
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| 3.2438 | 6.0 | 7254 | 3.0479 | 17.2072 | 8.0951 | 17.025 | 16.9644 | |
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| 3.2024 | 7.0 | 8463 | 3.0377 | 17.3692 | 8.1843 | 17.019 | 17.0006 | |
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| 3.1745 | 8.0 | 9672 | 3.0393 | 17.3313 | 8.1251 | 17.0359 | 16.9503 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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