---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-text2sql_v1
  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-text2sql_v1

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2541
- Rouge2 Precision: 0.8524
- Rouge2 Recall: 0.3329
- Rouge2 Fmeasure: 0.462

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 1.0   | 11   | 3.1289          | 0.0456           | 0.0134        | 0.0207          |
| No log        | 2.0   | 22   | 2.0536          | 0.0472           | 0.0134        | 0.0208          |
| No log        | 3.0   | 33   | 1.4151          | 0.0519           | 0.0149        | 0.0231          |
| No log        | 4.0   | 44   | 0.9640          | 0.0484           | 0.0134        | 0.0209          |
| No log        | 5.0   | 55   | 0.7020          | 0.4762           | 0.1867        | 0.2605          |
| No log        | 6.0   | 66   | 0.5500          | 0.6708           | 0.2613        | 0.3658          |
| No log        | 7.0   | 77   | 0.4783          | 0.7633           | 0.2985        | 0.415           |
| No log        | 8.0   | 88   | 0.3953          | 0.8121           | 0.3085        | 0.4324          |
| No log        | 9.0   | 99   | 0.3533          | 0.8308           | 0.3189        | 0.4461          |
| No log        | 10.0  | 110  | 0.3330          | 0.8068           | 0.2979        | 0.4262          |
| No log        | 11.0  | 121  | 0.3071          | 0.8378           | 0.323         | 0.4534          |
| No log        | 12.0  | 132  | 0.2937          | 0.8218           | 0.3121        | 0.4404          |
| No log        | 13.0  | 143  | 0.2794          | 0.8414           | 0.3305        | 0.4577          |
| No log        | 14.0  | 154  | 0.2741          | 0.8671           | 0.336         | 0.4669          |
| No log        | 15.0  | 165  | 0.2690          | 0.8635           | 0.337         | 0.4678          |
| No log        | 16.0  | 176  | 0.2627          | 0.8446           | 0.3341        | 0.462           |
| No log        | 17.0  | 187  | 0.2583          | 0.8379           | 0.3322        | 0.4589          |
| No log        | 18.0  | 198  | 0.2563          | 0.8527           | 0.339         | 0.4684          |
| No log        | 19.0  | 209  | 0.2544          | 0.8524           | 0.3329        | 0.462           |
| No log        | 20.0  | 220  | 0.2541          | 0.8524           | 0.3329        | 0.462           |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1