---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_pct_reverse
  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-v0.3_pct_reverse

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.8605

## 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: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.1177        | 0.0206 | 8    | 2.6702          |
| 8.9887        | 0.0413 | 16   | 9.0083          |
| 7.777         | 0.0619 | 24   | 7.6913          |
| 7.6327        | 0.0825 | 32   | 7.6181          |
| 7.6585        | 0.1032 | 40   | 7.6409          |
| 7.6813        | 0.1238 | 48   | 7.5593          |
| 7.6016        | 0.1444 | 56   | 7.5868          |
| 7.5595        | 0.1651 | 64   | 7.5960          |
| 7.7069        | 0.1857 | 72   | 7.5984          |
| 7.6285        | 0.2063 | 80   | 7.4589          |
| 7.5374        | 0.2270 | 88   | 7.4251          |
| 7.4161        | 0.2476 | 96   | 7.3111          |
| 7.3713        | 0.2682 | 104  | 7.2864          |
| 7.2921        | 0.2888 | 112  | 7.2224          |
| 7.2529        | 0.3095 | 120  | 7.1938          |
| 7.3559        | 0.3301 | 128  | 7.1139          |
| 7.1657        | 0.3507 | 136  | 7.0930          |
| 7.066         | 0.3714 | 144  | 7.0315          |
| 7.1481        | 0.3920 | 152  | 7.0332          |
| 7.0394        | 0.4126 | 160  | 7.0583          |
| 7.0685        | 0.4333 | 168  | 7.0682          |
| 6.9791        | 0.4539 | 176  | 6.9472          |
| 7.1428        | 0.4745 | 184  | 7.0126          |
| 7.1661        | 0.4952 | 192  | 6.9513          |
| 6.9757        | 0.5158 | 200  | 7.0717          |
| 6.9685        | 0.5364 | 208  | 6.9399          |
| 7.0811        | 0.5571 | 216  | 6.8879          |
| 7.0126        | 0.5777 | 224  | 6.9264          |
| 6.9712        | 0.5983 | 232  | 6.8394          |
| 6.9533        | 0.6190 | 240  | 6.9073          |
| 6.9744        | 0.6396 | 248  | 6.9239          |
| 7.1531        | 0.6602 | 256  | 6.9109          |
| 6.9527        | 0.6809 | 264  | 6.8941          |
| 7.1027        | 0.7015 | 272  | 6.9498          |
| 7.1718        | 0.7221 | 280  | 6.9495          |
| 7.0877        | 0.7427 | 288  | 6.9761          |
| 6.9879        | 0.7634 | 296  | 6.9905          |
| 6.9813        | 0.7840 | 304  | 6.9238          |
| 7.0798        | 0.8046 | 312  | 6.8707          |
| 7.0531        | 0.8253 | 320  | 6.8658          |
| 7.0518        | 0.8459 | 328  | 6.8576          |
| 7.127         | 0.8665 | 336  | 6.9017          |
| 6.9259        | 0.8872 | 344  | 6.8581          |
| 6.9477        | 0.9078 | 352  | 6.8727          |
| 7.0367        | 0.9284 | 360  | 6.8629          |
| 6.9114        | 0.9491 | 368  | 6.8469          |
| 7.0537        | 0.9697 | 376  | 6.8627          |
| 6.9656        | 0.9903 | 384  | 6.8605          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1