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

# NXAIR_M_mistral-7B

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6929

## 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: 0.00025
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1435        | 0.0702 | 100  | 1.1971          |
| 1.0993        | 0.1404 | 200  | 1.0390          |
| 1.0643        | 0.2107 | 300  | 0.9309          |
| 0.956         | 0.2809 | 400  | 0.9125          |
| 0.9906        | 0.3511 | 500  | 0.8591          |
| 0.9083        | 0.4213 | 600  | 0.8703          |
| 0.8951        | 0.4916 | 700  | 0.8179          |
| 0.8352        | 0.5618 | 800  | 0.7852          |
| 0.8472        | 0.6320 | 900  | 0.7772          |
| 0.8733        | 0.7022 | 1000 | 0.7447          |
| 0.7958        | 0.7725 | 1100 | 0.7082          |
| 0.8726        | 0.8427 | 1200 | 0.7125          |
| 0.804         | 0.9129 | 1300 | 0.6909          |
| 0.8467        | 0.9831 | 1400 | 0.7287          |
| 0.4705        | 1.0534 | 1500 | 0.6921          |
| 0.4864        | 1.1236 | 1600 | 0.6648          |
| 0.4535        | 1.1938 | 1700 | 0.6765          |
| 0.4542        | 1.2640 | 1800 | 0.6620          |
| 0.4789        | 1.3343 | 1900 | 0.6584          |
| 0.5154        | 1.4045 | 2000 | 0.6492          |
| 0.459         | 1.4747 | 2100 | 0.6647          |
| 0.5168        | 1.5449 | 2200 | 0.6484          |
| 0.483         | 1.6152 | 2300 | 0.6795          |
| 0.4768        | 1.6854 | 2400 | 0.6730          |
| 0.4821        | 1.7556 | 2500 | 0.6404          |
| 0.4929        | 1.8258 | 2600 | 0.6409          |
| 0.5438        | 1.8961 | 2700 | 0.6551          |
| 0.4598        | 1.9663 | 2800 | 0.6740          |
| 0.4902        | 2.0365 | 2900 | 0.7287          |
| 0.5058        | 2.1067 | 3000 | 0.7142          |
| 0.4615        | 2.1770 | 3100 | 0.6929          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1