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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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- 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-fine-tune |
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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-fine-tune |
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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: 2.5256 |
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- Rouge1: 0.0822 |
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- Rouge2: 0.0244 |
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- Rougel: 0.0813 |
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- Rougelsum: 0.0814 |
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- Gen Len: 18.9803 |
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- Chrf Score: 20.301 |
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- Chrf Char Order: 6 |
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- Chrf Word Order: 0 |
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- Chrf Beta: 2 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Chrf Score | Chrf Char Order | Chrf Word Order | Chrf Beta | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:----------:|:---------------:|:---------------:|:---------:| |
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| 3.5479 | 1.0 | 1951 | 2.7435 | 0.0672 | 0.021 | 0.0666 | 0.0667 | 18.9323 | 19.2495 | 6 | 0 | 2 | |
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| 3.1717 | 2.0 | 3902 | 2.6452 | 0.0746 | 0.0207 | 0.0738 | 0.0737 | 18.9814 | 20.1079 | 6 | 0 | 2 | |
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| 3.0151 | 3.0 | 5853 | 2.6014 | 0.0834 | 0.0243 | 0.0826 | 0.0823 | 18.9891 | 20.2875 | 6 | 0 | 2 | |
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| 2.95 | 4.0 | 7804 | 2.5647 | 0.0765 | 0.0218 | 0.0757 | 0.0757 | 18.981 | 20.2327 | 6 | 0 | 2 | |
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| 2.8592 | 5.0 | 9755 | 2.5480 | 0.0822 | 0.0242 | 0.0814 | 0.0813 | 18.9819 | 20.3982 | 6 | 0 | 2 | |
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| 2.8214 | 6.0 | 11706 | 2.5317 | 0.0841 | 0.0255 | 0.0831 | 0.083 | 18.9764 | 20.3935 | 6 | 0 | 2 | |
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| 2.789 | 7.0 | 13657 | 2.5256 | 0.0822 | 0.0244 | 0.0813 | 0.0814 | 18.9803 | 20.301 | 6 | 0 | 2 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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