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---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: t5-small-finetuned-wikisql
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-wikisql
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1247
- Model Preparation Time: 0.0049
- Rouge1 Precision: 0.873
- Rouge1 Recall: 0.873
- Rouge1 Fmeasure: 0.873
- Rouge2 Precision: 0.7718
- Rouge2 Recall: 0.7718
- Rouge2 Fmeasure: 0.7718
- Rougel Precision: 0.86
- Rougel Recall: 0.86
- Rougel Fmeasure: 0.86
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| 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 |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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