---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-text2sql-sagemaker
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/truskovskiyk/gpu-jobs-comparison/runs/uwp42gjd)
# phi-3-text2sql-sagemaker

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7747

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0      | 0    | 2.8740          |
| 1.3554        | 0.1072 | 500  | 0.8899          |
| 0.8559        | 0.2143 | 1000 | 0.8313          |
| 0.8154        | 0.3215 | 1500 | 0.8094          |
| 0.7986        | 0.4287 | 2000 | 0.7940          |
| 0.79          | 0.5358 | 2500 | 0.7870          |
| 0.7877        | 0.6430 | 3000 | 0.7806          |
| 0.7806        | 0.7502 | 3500 | 0.7769          |
| 0.773         | 0.8574 | 4000 | 0.7752          |
| 0.7737        | 0.9645 | 4500 | 0.7747          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.19.1