---
base_model: unsloth/mistral-7b-v0.3
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_pct_default_r16
  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_default_r16

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3](https://huggingface.co/unsloth/mistral-7b-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0180

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9646        | 0.0206 | 8    | 2.0348          |
| 2.0531        | 0.0413 | 16   | 2.0345          |
| 2.1168        | 0.0619 | 24   | 2.0464          |
| 2.0712        | 0.0825 | 32   | 2.0462          |
| 2.0779        | 0.1032 | 40   | 2.0510          |
| 2.0905        | 0.1238 | 48   | 2.0476          |
| 2.0624        | 0.1445 | 56   | 2.0475          |
| 2.0793        | 0.1651 | 64   | 2.0428          |
| 2.0559        | 0.1857 | 72   | 2.0521          |
| 2.0597        | 0.2064 | 80   | 2.0680          |
| 2.1235        | 0.2270 | 88   | 2.0849          |
| 2.14          | 0.2476 | 96   | 2.0772          |
| 2.1586        | 0.2683 | 104  | 2.0880          |
| 2.0974        | 0.2889 | 112  | 2.0837          |
| 2.1577        | 0.3096 | 120  | 2.0838          |
| 2.0998        | 0.3302 | 128  | 2.0899          |
| 2.1069        | 0.3508 | 136  | 2.0882          |
| 2.1621        | 0.3715 | 144  | 2.0846          |
| 2.1441        | 0.3921 | 152  | 2.0949          |
| 2.1355        | 0.4127 | 160  | 2.0859          |
| 2.084         | 0.4334 | 168  | 2.0871          |
| 2.1649        | 0.4540 | 176  | 2.0845          |
| 2.0651        | 0.4746 | 184  | 2.0719          |
| 2.1708        | 0.4953 | 192  | 2.0722          |
| 2.1311        | 0.5159 | 200  | 2.0677          |
| 2.1038        | 0.5366 | 208  | 2.0627          |
| 2.0804        | 0.5572 | 216  | 2.0757          |
| 2.0695        | 0.5778 | 224  | 2.0649          |
| 2.0961        | 0.5985 | 232  | 2.0643          |
| 2.0808        | 0.6191 | 240  | 2.0567          |
| 2.1337        | 0.6397 | 248  | 2.0557          |
| 2.0565        | 0.6604 | 256  | 2.0555          |
| 2.1184        | 0.6810 | 264  | 2.0497          |
| 2.0604        | 0.7017 | 272  | 2.0412          |
| 2.1099        | 0.7223 | 280  | 2.0384          |
| 2.1048        | 0.7429 | 288  | 2.0415          |
| 2.0692        | 0.7636 | 296  | 2.0340          |
| 2.0489        | 0.7842 | 304  | 2.0331          |
| 2.057         | 0.8048 | 312  | 2.0275          |
| 2.0485        | 0.8255 | 320  | 2.0224          |
| 2.0364        | 0.8461 | 328  | 2.0202          |
| 2.014         | 0.8667 | 336  | 2.0240          |
| 2.0656        | 0.8874 | 344  | 2.0236          |
| 2.0473        | 0.9080 | 352  | 2.0197          |
| 2.0279        | 0.9287 | 360  | 2.0180          |
| 2.0415        | 0.9493 | 368  | 2.0178          |
| 2.0419        | 0.9699 | 376  | 2.0178          |
| 2.0597        | 0.9906 | 384  | 2.0180          |


### Framework versions

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