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--- |
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license: mit |
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base_model: unicamp-dl/ptt5-base-portuguese-vocab |
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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: ptt5-base-portuguese-vocab-finetuned-xlsum-pt |
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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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# ptt5-base-portuguese-vocab-finetuned-xlsum-pt |
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This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0394 |
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- Rouge1: 17.6273 |
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- Rouge2: 16.731 |
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- Rougel: 17.6255 |
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- Rougelsum: 17.629 |
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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: 10 |
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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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| 0.0596 | 1.0 | 125 | 0.0352 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0314 | 2.0 | 250 | 0.0324 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0248 | 3.0 | 375 | 0.0312 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0213 | 4.0 | 500 | 0.0328 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0177 | 5.0 | 625 | 0.0322 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0153 | 6.0 | 750 | 0.0346 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0139 | 7.0 | 875 | 0.0379 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0125 | 8.0 | 1000 | 0.0360 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0113 | 9.0 | 1125 | 0.0372 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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| 0.0112 | 10.0 | 1250 | 0.0394 | 17.6273 | 16.731 | 17.6255 | 17.629 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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