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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: t5-base-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-base-wikisql
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0822
- Rouge2 Precision: 0.8552
- Rouge2 Recall: 0.7632
- Rouge2 Fmeasure: 0.7994
## 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: 100
- eval_batch_size: 100
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.3772 | 1.0 | 648 | 0.1194 | 0.8164 | 0.7266 | 0.7619 |
| 0.1367 | 2.0 | 1296 | 0.1029 | 0.8322 | 0.7413 | 0.777 |
| 0.1184 | 3.0 | 1944 | 0.0960 | 0.839 | 0.7477 | 0.7837 |
| 0.0999 | 4.0 | 2592 | 0.0920 | 0.8447 | 0.7527 | 0.789 |
| 0.0943 | 5.0 | 3240 | 0.0884 | 0.8473 | 0.7549 | 0.7913 |
| 0.0886 | 6.0 | 3888 | 0.0868 | 0.8494 | 0.7568 | 0.7933 |
| 0.0821 | 7.0 | 4536 | 0.0852 | 0.8516 | 0.7588 | 0.7954 |
| 0.0792 | 8.0 | 5184 | 0.0845 | 0.8534 | 0.7605 | 0.7971 |
| 0.0765 | 9.0 | 5832 | 0.0836 | 0.8539 | 0.7622 | 0.7983 |
| 0.0741 | 10.0 | 6480 | 0.0825 | 0.8536 | 0.7616 | 0.7978 |
| 0.0708 | 11.0 | 7128 | 0.0827 | 0.8548 | 0.7625 | 0.7989 |
| 0.0693 | 12.0 | 7776 | 0.0822 | 0.8547 | 0.7629 | 0.799 |
| 0.0686 | 13.0 | 8424 | 0.0822 | 0.855 | 0.7631 | 0.7993 |
| 0.0672 | 14.0 | 9072 | 0.0823 | 0.8553 | 0.7633 | 0.7995 |
| 0.0664 | 15.0 | 9720 | 0.0822 | 0.8552 | 0.7632 | 0.7994 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.14.7
- Tokenizers 0.13.3
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