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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_no_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_no_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: 0.1014 |
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- Rouge2 Precision: 0.774 |
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- Rouge2 Recall: 0.7029 |
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- Rouge2 Fmeasure: 0.731 |
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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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| 0.1507 | 1.0 | 8637 | 0.1284 | 0.7172 | 0.6444 | 0.673 | |
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| 0.1214 | 2.0 | 17274 | 0.1125 | 0.7391 | 0.6666 | 0.6954 | |
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| 0.1049 | 3.0 | 25911 | 0.1070 | 0.7514 | 0.6775 | 0.7069 | |
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| 0.0951 | 4.0 | 34548 | 0.1035 | 0.7558 | 0.6832 | 0.712 | |
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| 0.0893 | 5.0 | 43185 | 0.1019 | 0.7627 | 0.6903 | 0.7189 | |
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| 0.0854 | 6.0 | 51822 | 0.1010 | 0.766 | 0.6933 | 0.7222 | |
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| 0.0794 | 7.0 | 60459 | 0.1001 | 0.7672 | 0.6951 | 0.7237 | |
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| 0.0719 | 8.0 | 69096 | 0.0999 | 0.7703 | 0.698 | 0.7267 | |
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| 0.0713 | 9.0 | 77733 | 0.1002 | 0.77 | 0.6983 | 0.7268 | |
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| 0.067 | 10.0 | 86370 | 0.1004 | 0.7726 | 0.7006 | 0.7291 | |
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| 0.0649 | 11.0 | 95007 | 0.1005 | 0.773 | 0.7017 | 0.7299 | |
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| 0.0636 | 12.0 | 103644 | 0.1009 | 0.7733 | 0.7018 | 0.7301 | |
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| 0.0614 | 13.0 | 112281 | 0.1009 | 0.7735 | 0.7021 | 0.7303 | |
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| 0.0608 | 14.0 | 120918 | 0.1012 | 0.7737 | 0.7028 | 0.7308 | |
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| 0.06 | 15.0 | 129555 | 0.1014 | 0.774 | 0.7029 | 0.731 | |
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### Framework versions |
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- Transformers 4.38.2 |
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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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