peft safetensors trl sft generated_from_trainer dataset:generator base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- generator
model-index:
- name: mistral7bit-lora-sql
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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: 0.3640

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7533        | 0.06  | 20   | 0.5169          |
| 0.4806        | 0.11  | 40   | 0.4338          |
| 0.4285        | 0.17  | 60   | 0.4055          |
| 0.403         | 0.23  | 80   | 0.3944          |
| 0.3969        | 0.28  | 100  | 0.3869          |
| 0.3898        | 0.34  | 120  | 0.3813          |
| 0.3836        | 0.4   | 140  | 0.3766          |
| 0.3786        | 0.45  | 160  | 0.3726          |
| 0.3708        | 0.51  | 180  | 0.3675          |
| 0.3681        | 0.56  | 200  | 0.3643          |
| 0.3622        | 0.62  | 220  | 0.3631          |
| 0.3626        | 0.68  | 240  | 0.3640          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2