---
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: shawgpt-ft-lr2e-05-wd0.01
  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. -->

# shawgpt-ft-lr2e-05-wd0.01

This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8444

## 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: 2e-05
- 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_steps: 2
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 4.6427        | 0.9231  | 3    | 4.2081          |
| 4.5689        | 1.8462  | 6    | 4.1561          |
| 4.5192        | 2.7692  | 9    | 4.1061          |
| 3.3371        | 4.0     | 13   | 4.0411          |
| 4.4042        | 4.9231  | 16   | 3.9947          |
| 4.328         | 5.8462  | 19   | 3.9542          |
| 4.2913        | 6.7692  | 22   | 3.9199          |
| 3.168         | 8.0     | 26   | 3.8843          |
| 4.199         | 8.9231  | 29   | 3.8648          |
| 4.1898        | 9.8462  | 32   | 3.8517          |
| 4.1757        | 10.7692 | 35   | 3.8450          |
| 0.9827        | 11.0769 | 36   | 3.8444          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.19.1