---
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: 1.1371

## 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: 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_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1548        | 0.0262 | 4    | 1.1975          |
| 1.1117        | 0.0523 | 8    | 1.1750          |
| 1.1638        | 0.0785 | 12   | 1.1670          |
| 1.0902        | 0.1047 | 16   | 1.1675          |
| 1.1292        | 0.1308 | 20   | 1.1671          |
| 1.0469        | 0.1570 | 24   | 1.1621          |
| 1.2005        | 0.1832 | 28   | 1.1638          |
| 1.1491        | 0.2093 | 32   | 1.1638          |
| 1.0749        | 0.2355 | 36   | 1.1475          |
| 1.1758        | 0.2617 | 40   | 1.1525          |
| 1.1511        | 0.2878 | 44   | 1.1410          |
| 1.1229        | 0.3140 | 48   | 1.1532          |
| 1.1349        | 0.3401 | 52   | 1.1592          |
| 1.1116        | 0.3663 | 56   | 1.1465          |
| 1.1127        | 0.3925 | 60   | 1.1517          |
| 1.1709        | 0.4186 | 64   | 1.1460          |
| 1.0574        | 0.4448 | 68   | 1.1504          |
| 1.0794        | 0.4710 | 72   | 1.1414          |
| 1.0711        | 0.4971 | 76   | 1.1485          |
| 1.1984        | 0.5233 | 80   | 1.1544          |
| 1.0625        | 0.5495 | 84   | 1.1346          |
| 1.151         | 0.5756 | 88   | 1.1728          |
| 1.1977        | 0.6018 | 92   | 1.1364          |
| 1.1757        | 0.6280 | 96   | 1.1418          |
| 1.1191        | 0.6541 | 100  | 1.1487          |
| 1.1415        | 0.6803 | 104  | 1.1431          |
| 1.1272        | 0.7065 | 108  | 1.1399          |
| 1.0134        | 0.7326 | 112  | 1.1431          |
| 1.09          | 0.7588 | 116  | 1.1261          |
| 1.0848        | 0.7850 | 120  | 1.1346          |
| 1.1346        | 0.8111 | 124  | 1.1401          |
| 1.1336        | 0.8373 | 128  | 1.1371          |
| 1.1458        | 0.8635 | 132  | 1.1338          |
| 1.0835        | 0.8896 | 136  | 1.1334          |
| 1.1795        | 0.9158 | 140  | 1.1345          |
| 1.0422        | 0.9419 | 144  | 1.1359          |
| 1.0608        | 0.9681 | 148  | 1.1367          |
| 1.2045        | 0.9943 | 152  | 1.1371          |


### Framework versions

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