---
base_model: mistralai/Mistral-7B-v0.1
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral7bit-lora-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. -->

# mistral7bit-lora-sql

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3405

## 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: 8
- eval_batch_size: 8
- seed: 1399
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7523        | 0.0565 | 20   | 0.5037          |
| 0.4763        | 0.1129 | 40   | 0.4221          |
| 0.4231        | 0.1694 | 60   | 0.3944          |
| 0.4051        | 0.2258 | 80   | 0.3833          |
| 0.396         | 0.2823 | 100  | 0.3756          |
| 0.3885        | 0.3387 | 120  | 0.3717          |
| 0.3829        | 0.3952 | 140  | 0.3651          |
| 0.3752        | 0.4517 | 160  | 0.3605          |
| 0.3752        | 0.5081 | 180  | 0.3565          |
| 0.3688        | 0.5646 | 200  | 0.3551          |
| 0.3655        | 0.6210 | 220  | 0.3530          |
| 0.3596        | 0.6775 | 240  | 0.3472          |
| 0.3565        | 0.7339 | 260  | 0.3460          |
| 0.3556        | 0.7904 | 280  | 0.3448          |
| 0.3553        | 0.8469 | 300  | 0.3440          |
| 0.3496        | 0.9033 | 320  | 0.3424          |
| 0.3446        | 0.9598 | 340  | 0.3405          |
| 0.3328        | 1.0162 | 360  | 0.3402          |
| 0.3035        | 1.0727 | 380  | 0.3405          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.2.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1