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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikisql |
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model-index: |
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- name: t5-small-finetuned-wikisql |
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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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# t5-small-finetuned-wikisql |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikisql dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1247 |
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- Model Preparation Time: 0.0049 |
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- Rouge1 Precision: 0.873 |
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- Rouge1 Recall: 0.873 |
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- Rouge1 Fmeasure: 0.873 |
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- Rouge2 Precision: 0.7718 |
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- Rouge2 Recall: 0.7718 |
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- Rouge2 Fmeasure: 0.7718 |
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- Rougel Precision: 0.86 |
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- Rougel Recall: 0.86 |
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- Rougel Fmeasure: 0.86 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 0.1942 | 1.0 | 4049 | 0.1561 | 0.0049 | 0.8629 | 0.8629 | 0.8629 | 0.7471 | 0.7471 | 0.7471 | 0.8471 | 0.8471 | 0.8471 | |
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| 0.1646 | 2.0 | 8098 | 0.1373 | 0.0049 | 0.8697 | 0.8697 | 0.8697 | 0.763 | 0.763 | 0.763 | 0.8555 | 0.8555 | 0.8555 | |
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| 0.147 | 3.0 | 12147 | 0.1297 | 0.0049 | 0.8723 | 0.8723 | 0.8723 | 0.7684 | 0.7684 | 0.7684 | 0.8588 | 0.8588 | 0.8588 | |
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| 0.1412 | 4.0 | 16196 | 0.1256 | 0.0049 | 0.8725 | 0.8725 | 0.8725 | 0.7712 | 0.7712 | 0.7712 | 0.8595 | 0.8595 | 0.8595 | |
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| 0.14 | 5.0 | 20245 | 0.1247 | 0.0049 | 0.873 | 0.873 | 0.873 | 0.7718 | 0.7718 | 0.7718 | 0.86 | 0.86 | 0.86 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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