---
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
  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

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: 1.1309

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1655        | 0.0261 | 4    | 1.1621          |
| 1.0912        | 0.0523 | 8    | 1.1461          |
| 1.1696        | 0.0784 | 12   | 1.1691          |
| 1.0845        | 0.1046 | 16   | 1.1686          |
| 1.1548        | 0.1307 | 20   | 1.1627          |
| 1.0495        | 0.1569 | 24   | 1.1600          |
| 1.192         | 0.1830 | 28   | 1.1692          |
| 1.1397        | 0.2092 | 32   | 1.1666          |
| 1.0956        | 0.2353 | 36   | 1.1564          |
| 1.1748        | 0.2614 | 40   | 1.1647          |
| 1.1924        | 0.2876 | 44   | 1.1664          |
| 1.1258        | 0.3137 | 48   | 1.1596          |
| 1.1319        | 0.3399 | 52   | 1.1619          |
| 1.1099        | 0.3660 | 56   | 1.1577          |
| 1.122         | 0.3922 | 60   | 1.1573          |
| 1.1749        | 0.4183 | 64   | 1.1538          |
| 1.0708        | 0.4444 | 68   | 1.1579          |
| 1.0763        | 0.4706 | 72   | 1.1419          |
| 1.0635        | 0.4967 | 76   | 1.1494          |
| 1.1717        | 0.5229 | 80   | 1.1519          |
| 1.0674        | 0.5490 | 84   | 1.1404          |
| 1.1492        | 0.5752 | 88   | 1.1620          |
| 1.2029        | 0.6013 | 92   | 1.1477          |
| 1.1744        | 0.6275 | 96   | 1.1346          |
| 1.104         | 0.6536 | 100  | 1.1438          |
| 1.1398        | 0.6797 | 104  | 1.1436          |
| 1.1296        | 0.7059 | 108  | 1.1409          |
| 1.0167        | 0.7320 | 112  | 1.1469          |
| 1.1048        | 0.7582 | 116  | 1.1396          |
| 1.1004        | 0.7843 | 120  | 1.1358          |
| 1.1283        | 0.8105 | 124  | 1.1333          |
| 1.1287        | 0.8366 | 128  | 1.1322          |
| 1.1421        | 0.8627 | 132  | 1.1315          |
| 1.0848        | 0.8889 | 136  | 1.1303          |
| 1.184         | 0.9150 | 140  | 1.1300          |
| 1.0453        | 0.9412 | 144  | 1.1304          |
| 1.0604        | 0.9673 | 148  | 1.1307          |
| 1.2116        | 0.9935 | 152  | 1.1309          |


### Framework versions

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