---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: Finetune-test4
  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. -->

# Finetune-test4

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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1223

## 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
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.767         | 0.9956  | 56   | 0.5333          |
| 0.4313        | 1.9911  | 112  | 0.4449          |
| 0.3107        | 2.9867  | 168  | 0.4640          |
| 0.2198        | 4.0     | 225  | 0.5196          |
| 0.1633        | 4.9956  | 281  | 0.5811          |
| 0.1209        | 5.9911  | 337  | 0.6468          |
| 0.0944        | 6.9867  | 393  | 0.6891          |
| 0.0745        | 8.0     | 450  | 0.7297          |
| 0.064         | 8.9956  | 506  | 0.7844          |
| 0.0557        | 9.9911  | 562  | 0.8384          |
| 0.0489        | 10.9867 | 618  | 0.8632          |
| 0.0433        | 12.0    | 675  | 0.9223          |
| 0.0413        | 12.9956 | 731  | 0.9526          |
| 0.0389        | 13.9911 | 787  | 0.9552          |
| 0.0375        | 14.9867 | 843  | 1.0303          |
| 0.0355        | 16.0    | 900  | 1.0489          |
| 0.0355        | 16.9956 | 956  | 1.0804          |
| 0.0347        | 17.9911 | 1012 | 1.0983          |
| 0.0341        | 18.9867 | 1068 | 1.1147          |
| 0.0328        | 19.9111 | 1120 | 1.1223          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1