---
license: other
base_model: microsoft/phi-1_5
tags:
- generated_from_trainer
model-index:
- name: phi-1_5-finetuned-SQL
  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. -->

# phi-1_5-finetuned-SQL

This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5295

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 6000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3757        | 0.04  | 100  | 2.0747          |
| 2.0269        | 0.08  | 200  | 1.9990          |
| 1.9535        | 0.12  | 300  | 1.9450          |
| 1.9136        | 0.16  | 400  | 1.9067          |
| 1.892         | 0.2   | 500  | 1.8757          |
| 1.8753        | 0.24  | 600  | 1.8574          |
| 1.8507        | 0.28  | 700  | 1.8359          |
| 1.8759        | 0.32  | 800  | 1.8167          |
| 1.8166        | 0.36  | 900  | 1.8054          |
| 1.8224        | 0.4   | 1000 | 1.7818          |
| 1.7852        | 0.44  | 1100 | 1.7814          |
| 1.8164        | 0.48  | 1200 | 1.7664          |
| 1.7632        | 0.52  | 1300 | 1.7598          |
| 1.8485        | 0.56  | 1400 | 1.7439          |
| 1.7712        | 0.6   | 1500 | 1.7303          |
| 1.7632        | 0.64  | 1600 | 1.7277          |
| 1.7378        | 0.68  | 1700 | 1.7135          |
| 1.7581        | 0.72  | 1800 | 1.7075          |
| 1.7261        | 0.76  | 1900 | 1.6933          |
| 1.7243        | 0.8   | 2000 | 1.6891          |
| 1.7311        | 0.84  | 2100 | 1.6837          |
| 1.7554        | 0.88  | 2200 | 1.6808          |
| 1.7026        | 0.92  | 2300 | 1.6646          |
| 1.7193        | 0.96  | 2400 | 1.6664          |
| 1.6861        | 1.0   | 2500 | 1.6577          |
| 1.68          | 1.04  | 2600 | 1.6470          |
| 1.5931        | 1.08  | 2700 | 1.6425          |
| 1.6655        | 1.12  | 2800 | 1.6352          |
| 1.629         | 1.16  | 2900 | 1.6298          |
| 1.6567        | 1.2   | 3000 | 1.6236          |
| 1.6225        | 1.24  | 3100 | 1.6242          |
| 1.6249        | 1.28  | 3200 | 1.6150          |
| 1.6263        | 1.32  | 3300 | 1.6077          |
| 1.6055        | 1.36  | 3400 | 1.6034          |
| 1.6338        | 1.4   | 3500 | 1.5996          |
| 1.6032        | 1.44  | 3600 | 1.5947          |
| 1.6447        | 1.48  | 3700 | 1.5882          |
| 1.6063        | 1.52  | 3800 | 1.5877          |
| 1.5933        | 1.56  | 3900 | 1.5850          |
| 1.6267        | 1.6   | 4000 | 1.5814          |
| 1.6151        | 1.64  | 4100 | 1.5709          |
| 1.6047        | 1.68  | 4200 | 1.5683          |
| 1.5811        | 1.72  | 4300 | 1.5661          |
| 1.5877        | 1.76  | 4400 | 1.5648          |
| 1.6321        | 1.8   | 4500 | 1.5645          |
| 1.5969        | 1.84  | 4600 | 1.5584          |
| 1.5971        | 1.88  | 4700 | 1.5565          |
| 1.622         | 1.92  | 4800 | 1.5547          |
| 1.6265        | 1.96  | 4900 | 1.5496          |
| 1.6145        | 2.0   | 5000 | 1.5466          |
| 1.526         | 2.04  | 5100 | 1.5427          |
| 1.5793        | 2.08  | 5200 | 1.5390          |
| 1.5714        | 2.12  | 5300 | 1.5375          |
| 1.5228        | 2.16  | 5400 | 1.5360          |
| 1.5383        | 2.2   | 5500 | 1.5343          |
| 1.5117        | 2.24  | 5600 | 1.5322          |
| 1.5427        | 2.28  | 5700 | 1.5316          |
| 1.4959        | 2.32  | 5800 | 1.5306          |
| 1.5456        | 2.36  | 5900 | 1.5299          |
| 1.5175        | 2.4   | 6000 | 1.5295          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1