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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ALL_mt5-base_10_wikiSQL_sch |
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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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# ALL_mt5-base_10_wikiSQL_sch |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0566 |
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- Rouge2 Precision: 0.8825 |
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- Rouge2 Recall: 0.802 |
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- Rouge2 Fmeasure: 0.8343 |
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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: 5e-05 |
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- train_batch_size: 15 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 0.0789 | 1.0 | 8637 | 0.0678 | 0.859 | 0.7788 | 0.8103 | |
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| 0.0683 | 2.0 | 17274 | 0.0613 | 0.8688 | 0.7867 | 0.8196 | |
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| 0.0587 | 3.0 | 25911 | 0.0595 | 0.8726 | 0.7917 | 0.8241 | |
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| 0.0546 | 4.0 | 34548 | 0.0578 | 0.8771 | 0.7957 | 0.8284 | |
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| 0.0499 | 5.0 | 43185 | 0.0572 | 0.8793 | 0.7981 | 0.8308 | |
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| 0.0484 | 6.0 | 51822 | 0.0568 | 0.8797 | 0.7992 | 0.8315 | |
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| 0.0447 | 7.0 | 60459 | 0.0565 | 0.8809 | 0.8003 | 0.8326 | |
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| 0.0415 | 8.0 | 69096 | 0.0565 | 0.882 | 0.8013 | 0.8337 | |
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| 0.042 | 9.0 | 77733 | 0.0564 | 0.8822 | 0.8019 | 0.8341 | |
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| 0.0407 | 10.0 | 86370 | 0.0566 | 0.8825 | 0.802 | 0.8343 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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