---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.3
model-index:
- name: mistral_7b_v_Magiccoder_evol_10k_ortho
  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_v_Magiccoder_evol_10k_ortho

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1790

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.173         | 0.0261 | 4    | 1.2153          |
| 1.1501        | 0.0523 | 8    | 1.1905          |
| 1.19          | 0.0784 | 12   | 1.1831          |
| 1.0875        | 0.1046 | 16   | 1.1805          |
| 1.1648        | 0.1307 | 20   | 1.1844          |
| 1.077         | 0.1569 | 24   | 1.1861          |
| 1.2251        | 0.1830 | 28   | 1.1925          |
| 1.1615        | 0.2092 | 32   | 1.1922          |
| 1.1153        | 0.2353 | 36   | 1.1763          |
| 1.2024        | 0.2614 | 40   | 1.1803          |
| 1.2181        | 0.2876 | 44   | 1.1724          |
| 1.1503        | 0.3137 | 48   | 1.2055          |
| 1.1639        | 0.3399 | 52   | 1.1896          |
| 1.1405        | 0.3660 | 56   | 1.1827          |
| 1.177         | 0.3922 | 60   | 1.2037          |
| 1.1958        | 0.4183 | 64   | 1.1796          |
| 1.1044        | 0.4444 | 68   | 1.1970          |
| 1.1115        | 0.4706 | 72   | 1.1735          |
| 1.1152        | 0.4967 | 76   | 1.2061          |
| 1.2009        | 0.5229 | 80   | 1.1671          |
| 1.1154        | 0.5490 | 84   | 1.1960          |
| 1.1739        | 0.5752 | 88   | 1.1892          |
| 1.2224        | 0.6013 | 92   | 1.1764          |
| 1.2229        | 0.6275 | 96   | 1.1926          |
| 1.1573        | 0.6536 | 100  | 1.1849          |
| 1.1629        | 0.6797 | 104  | 1.1787          |
| 1.1855        | 0.7059 | 108  | 1.1955          |
| 1.0586        | 0.7320 | 112  | 1.1814          |
| 1.1258        | 0.7582 | 116  | 1.1631          |
| 1.1273        | 0.7843 | 120  | 1.1787          |
| 1.1869        | 0.8105 | 124  | 1.1873          |
| 1.1765        | 0.8366 | 128  | 1.1852          |
| 1.1954        | 0.8627 | 132  | 1.1809          |
| 1.1277        | 0.8889 | 136  | 1.1763          |
| 1.2109        | 0.9150 | 140  | 1.1747          |
| 1.0842        | 0.9412 | 144  | 1.1771          |
| 1.0941        | 0.9673 | 148  | 1.1787          |
| 1.2413        | 0.9935 | 152  | 1.1790          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1