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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: EN_mrm8488_spider |
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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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# EN_mrm8488_spider |
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This model is a fine-tuned version of [mrm8488/t5-small-finetuned-wikiSQL](https://huggingface.co/mrm8488/t5-small-finetuned-wikiSQL) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1002 |
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- Rouge2 Precision: 0.0364 |
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- Rouge2 Recall: 0.0288 |
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- Rouge2 Fmeasure: 0.0266 |
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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: 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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| No log | 1.0 | 438 | 0.4103 | 0.3532 | 0.1547 | 0.194 | |
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| 0.9639 | 2.0 | 876 | 0.2544 | 0.189 | 0.086 | 0.1038 | |
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| 0.3388 | 3.0 | 1314 | 0.1954 | 0.1365 | 0.0641 | 0.0768 | |
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| 0.2255 | 4.0 | 1752 | 0.1614 | 0.0644 | 0.0377 | 0.0407 | |
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| 0.1673 | 5.0 | 2190 | 0.1412 | 0.0675 | 0.0443 | 0.0467 | |
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| 0.1356 | 6.0 | 2628 | 0.1344 | 0.0528 | 0.0361 | 0.0366 | |
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| 0.1148 | 7.0 | 3066 | 0.1255 | 0.0476 | 0.0333 | 0.0338 | |
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| 0.0998 | 8.0 | 3504 | 0.1167 | 0.0513 | 0.0389 | 0.0374 | |
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| 0.0998 | 9.0 | 3942 | 0.1107 | 0.0619 | 0.0447 | 0.0439 | |
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| 0.088 | 10.0 | 4380 | 0.1092 | 0.0529 | 0.0412 | 0.0384 | |
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| 0.0816 | 11.0 | 4818 | 0.1047 | 0.0478 | 0.0358 | 0.0334 | |
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| 0.0742 | 12.0 | 5256 | 0.1015 | 0.0386 | 0.0306 | 0.028 | |
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| 0.071 | 13.0 | 5694 | 0.1018 | 0.0384 | 0.0301 | 0.0281 | |
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| 0.0674 | 14.0 | 6132 | 0.1004 | 0.0344 | 0.0279 | 0.0256 | |
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| 0.0674 | 15.0 | 6570 | 0.1002 | 0.0364 | 0.0288 | 0.0266 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.7.dev0 |
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- Tokenizers 0.13.3 |
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