---
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_ortho_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_ortho_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: 2.0091

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9566        | 0.0206 | 8    | 2.0118          |
| 2.0191        | 0.0413 | 16   | 1.9983          |
| 2.0779        | 0.0619 | 24   | 2.0212          |
| 2.0339        | 0.0825 | 32   | 2.0205          |
| 2.0429        | 0.1032 | 40   | 2.0132          |
| 2.0601        | 0.1238 | 48   | 2.0219          |
| 2.041         | 0.1445 | 56   | 2.0171          |
| 2.0602        | 0.1651 | 64   | 2.0230          |
| 2.0341        | 0.1857 | 72   | 2.0311          |
| 2.0378        | 0.2064 | 80   | 2.0319          |
| 2.0961        | 0.2270 | 88   | 2.0402          |
| 2.106         | 0.2476 | 96   | 2.0208          |
| 2.1219        | 0.2683 | 104  | 2.0328          |
| 2.0569        | 0.2889 | 112  | 2.0528          |
| 2.1062        | 0.3096 | 120  | 2.0355          |
| 2.0522        | 0.3302 | 128  | 2.0365          |
| 2.0631        | 0.3508 | 136  | 2.0300          |
| 2.1052        | 0.3715 | 144  | 2.0409          |
| 2.0875        | 0.3921 | 152  | 2.0454          |
| 2.0854        | 0.4127 | 160  | 2.0273          |
| 2.0533        | 0.4334 | 168  | 2.0529          |
| 2.1096        | 0.4540 | 176  | 2.0373          |
| 2.0288        | 0.4746 | 184  | 2.0289          |
| 2.1344        | 0.4953 | 192  | 2.0375          |
| 2.0952        | 0.5159 | 200  | 2.0445          |
| 2.0613        | 0.5366 | 208  | 2.0374          |
| 2.0441        | 0.5572 | 216  | 2.0225          |
| 2.0493        | 0.5778 | 224  | 2.0380          |
| 2.0568        | 0.5985 | 232  | 2.0219          |
| 2.0477        | 0.6191 | 240  | 2.0261          |
| 2.1065        | 0.6397 | 248  | 2.0310          |
| 2.0245        | 0.6604 | 256  | 2.0208          |
| 2.1013        | 0.6810 | 264  | 2.0270          |
| 2.0356        | 0.7017 | 272  | 2.0205          |
| 2.0815        | 0.7223 | 280  | 2.0117          |
| 2.0898        | 0.7429 | 288  | 2.0175          |
| 2.0529        | 0.7636 | 296  | 2.0171          |
| 2.0281        | 0.7842 | 304  | 2.0134          |
| 2.0473        | 0.8048 | 312  | 2.0150          |
| 2.0315        | 0.8255 | 320  | 2.0088          |
| 2.0215        | 0.8461 | 328  | 2.0071          |
| 2.0003        | 0.8667 | 336  | 2.0093          |
| 2.0561        | 0.8874 | 344  | 2.0136          |
| 2.0407        | 0.9080 | 352  | 2.0132          |
| 2.0257        | 0.9287 | 360  | 2.0105          |
| 2.0294        | 0.9493 | 368  | 2.0090          |
| 2.0321        | 0.9699 | 376  | 2.0089          |
| 2.0516        | 0.9906 | 384  | 2.0091          |


### Framework versions

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