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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4213 |
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- Rouge1: 31.833 |
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- Rouge2: 11.5704 |
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- Rougel: 28.3537 |
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- Rougelsum: 29.7517 |
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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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| 12.421 | 1.0 | 185 | 4.1761 | 8.5214 | 1.3412 | 8.1063 | 8.2251 | |
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| 4.6683 | 2.0 | 370 | 2.8343 | 20.6485 | 7.1917 | 18.6741 | 19.4706 | |
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| 3.6666 | 3.0 | 555 | 2.5616 | 20.3673 | 6.1998 | 18.2531 | 19.0305 | |
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| 3.3157 | 4.0 | 740 | 2.5002 | 28.4326 | 11.0801 | 25.391 | 26.4882 | |
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| 3.1834 | 5.0 | 925 | 2.4586 | 29.0975 | 11.3058 | 26.0004 | 27.5342 | |
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| 3.0983 | 6.0 | 1110 | 2.4191 | 31.5865 | 11.3633 | 27.6063 | 29.6726 | |
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| 3.0338 | 7.0 | 1295 | 2.4258 | 31.845 | 11.9743 | 28.3534 | 29.8196 | |
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| 2.9805 | 8.0 | 1480 | 2.4213 | 31.833 | 11.5704 | 28.3537 | 29.7517 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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