---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: SQL_Final_RunPod_Last
  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. -->

# SQL_Final_RunPod_Last

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0215
- Bleu: 44.256
- Gen Len: 18.9114

## 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: 0.0003
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.2055        | 0.12  | 1000  | 0.0917          | 42.8594 | 18.8938 |
| 0.1187        | 0.23  | 2000  | 0.0709          | 43.1637 | 18.8915 |
| 0.1007        | 0.35  | 3000  | 0.0602          | 43.4304 | 18.9088 |
| 0.0869        | 0.46  | 4000  | 0.0559          | 43.4636 | 18.8961 |
| 0.0792        | 0.58  | 5000  | 0.0497          | 43.5366 | 18.9063 |
| 0.0736        | 0.69  | 6000  | 0.0464          | 43.5769 | 18.9016 |
| 0.0672        | 0.81  | 7000  | 0.0435          | 43.7471 | 18.9068 |
| 0.0635        | 0.93  | 8000  | 0.0403          | 43.781  | 18.9073 |
| 0.0564        | 1.04  | 9000  | 0.0389          | 43.7054 | 18.9029 |
| 0.0493        | 1.16  | 10000 | 0.0376          | 43.8362 | 18.9063 |
| 0.0479        | 1.27  | 11000 | 0.0367          | 43.8514 | 18.9126 |
| 0.0465        | 1.39  | 12000 | 0.0350          | 43.8365 | 18.9078 |
| 0.0449        | 1.5   | 13000 | 0.0335          | 43.8878 | 18.9042 |
| 0.0419        | 1.62  | 14000 | 0.0324          | 43.9035 | 18.9075 |
| 0.0426        | 1.74  | 15000 | 0.0314          | 43.9272 | 18.906  |
| 0.0405        | 1.85  | 16000 | 0.0302          | 44.0143 | 18.9087 |
| 0.039         | 1.97  | 17000 | 0.0291          | 43.9392 | 18.9089 |
| 0.0327        | 2.08  | 18000 | 0.0286          | 44.0248 | 18.9087 |
| 0.0311        | 2.2   | 19000 | 0.0288          | 44.0732 | 18.9119 |
| 0.0302        | 2.31  | 20000 | 0.0282          | 44.061  | 18.9055 |
| 0.029         | 2.43  | 21000 | 0.0279          | 44.0681 | 18.9121 |
| 0.0297        | 2.55  | 22000 | 0.0267          | 44.0958 | 18.91   |
| 0.0284        | 2.66  | 23000 | 0.0259          | 44.1215 | 18.9121 |
| 0.0272        | 2.78  | 24000 | 0.0259          | 44.0752 | 18.9113 |
| 0.0273        | 2.89  | 25000 | 0.0253          | 44.1104 | 18.909  |
| 0.0265        | 3.01  | 26000 | 0.0253          | 44.1262 | 18.9095 |
| 0.0215        | 3.12  | 27000 | 0.0251          | 44.137  | 18.9119 |
| 0.0215        | 3.24  | 28000 | 0.0246          | 44.1382 | 18.9096 |
| 0.0215        | 3.36  | 29000 | 0.0244          | 44.1806 | 18.9088 |
| 0.0206        | 3.47  | 30000 | 0.0237          | 44.169  | 18.911  |
| 0.0202        | 3.59  | 31000 | 0.0243          | 44.1469 | 18.9096 |
| 0.0204        | 3.7   | 32000 | 0.0231          | 44.1405 | 18.9116 |
| 0.0193        | 3.82  | 33000 | 0.0230          | 44.1613 | 18.9116 |
| 0.0196        | 3.94  | 34000 | 0.0226          | 44.197  | 18.9117 |
| 0.0177        | 4.05  | 35000 | 0.0228          | 44.1942 | 18.9102 |
| 0.0155        | 4.17  | 36000 | 0.0230          | 44.2241 | 18.9118 |
| 0.0159        | 4.28  | 37000 | 0.0226          | 44.2219 | 18.9107 |
| 0.0151        | 4.4   | 38000 | 0.0221          | 44.212  | 18.912  |
| 0.0149        | 4.51  | 39000 | 0.0222          | 44.2743 | 18.9115 |
| 0.0154        | 4.63  | 40000 | 0.0216          | 44.2636 | 18.9121 |
| 0.0149        | 4.75  | 41000 | 0.0215          | 44.2805 | 18.913  |
| 0.0146        | 4.86  | 42000 | 0.0216          | 44.2681 | 18.9125 |
| 0.0145        | 4.98  | 43000 | 0.0215          | 44.256  | 18.9114 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3