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

# Mistral-7B-Instruct-v0.2-GPTQ_retrained_NF_ToN_IoT_and_IoV

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: 0.2868

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.3006        | 1.0   | 6    | 2.3850          |
| 2.7433        | 2.0   | 12   | 2.2173          |
| 2.0996        | 3.0   | 18   | 2.0360          |
| 1.8643        | 4.0   | 24   | 1.8737          |
| 1.6957        | 5.0   | 30   | 1.6282          |
| 1.5218        | 6.0   | 36   | 1.3941          |
| 1.3533        | 7.0   | 42   | 1.1838          |
| 1.2254        | 8.0   | 48   | 0.9170          |
| 1.0833        | 9.0   | 54   | 0.7903          |
| 0.9952        | 10.0  | 60   | 0.6717          |
| 0.9268        | 11.0  | 66   | 0.5796          |
| 0.8677        | 12.0  | 72   | 0.5221          |
| 0.8085        | 13.0  | 78   | 0.4615          |
| 0.7681        | 14.0  | 84   | 0.3964          |
| 0.7376        | 15.0  | 90   | 0.3510          |
| 0.7131        | 16.0  | 96   | 0.3303          |
| 0.6965        | 17.0  | 102  | 0.3086          |
| 0.6863        | 18.0  | 108  | 0.2997          |
| 0.677         | 19.0  | 114  | 0.2917          |
| 0.6732        | 20.0  | 120  | 0.2868          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1