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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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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_15_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_15_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: 0.0585 |
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- Rouge2 Precision: 0.8836 |
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- Rouge2 Recall: 0.8038 |
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- Rouge2 Fmeasure: 0.8358 |
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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: 15 |
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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: 15 |
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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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| 0.0796 | 1.0 | 8637 | 0.0675 | 0.8604 | 0.78 | 0.8122 | |
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| 0.0683 | 2.0 | 17274 | 0.0617 | 0.8681 | 0.7878 | 0.8199 | |
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| 0.0587 | 3.0 | 25911 | 0.0593 | 0.8733 | 0.7924 | 0.8248 | |
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| 0.0527 | 4.0 | 34548 | 0.0579 | 0.8776 | 0.795 | 0.8282 | |
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| 0.0478 | 5.0 | 43185 | 0.0573 | 0.8788 | 0.7981 | 0.8305 | |
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| 0.0453 | 6.0 | 51822 | 0.0571 | 0.8806 | 0.7999 | 0.8323 | |
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| 0.043 | 7.0 | 60459 | 0.0571 | 0.8816 | 0.8008 | 0.8333 | |
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| 0.0399 | 8.0 | 69096 | 0.0570 | 0.881 | 0.8006 | 0.8329 | |
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| 0.0389 | 9.0 | 77733 | 0.0573 | 0.8823 | 0.8019 | 0.8343 | |
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| 0.0363 | 10.0 | 86370 | 0.0573 | 0.8828 | 0.8025 | 0.8347 | |
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| 0.0366 | 11.0 | 95007 | 0.0580 | 0.8835 | 0.8028 | 0.8352 | |
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| 0.0333 | 12.0 | 103644 | 0.0579 | 0.8836 | 0.8032 | 0.8355 | |
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| 0.0325 | 13.0 | 112281 | 0.0581 | 0.8833 | 0.8036 | 0.8356 | |
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| 0.0327 | 14.0 | 120918 | 0.0585 | 0.8839 | 0.8039 | 0.836 | |
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| 0.0306 | 15.0 | 129555 | 0.0585 | 0.8836 | 0.8038 | 0.8358 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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