---
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: 1.1499

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1885        | 0.0262 | 4    | 1.1900          |
| 1.0966        | 0.0523 | 8    | 1.1442          |
| 1.1468        | 0.0785 | 12   | 1.1514          |
| 1.0845        | 0.1047 | 16   | 1.1671          |
| 1.1413        | 0.1308 | 20   | 1.1635          |
| 1.0557        | 0.1570 | 24   | 1.1689          |
| 1.1949        | 0.1832 | 28   | 1.1682          |
| 1.149         | 0.2093 | 32   | 1.1674          |
| 1.0952        | 0.2355 | 36   | 1.1541          |
| 1.1551        | 0.2617 | 40   | 1.1687          |
| 1.1864        | 0.2878 | 44   | 1.1547          |
| 1.119         | 0.3140 | 48   | 1.1576          |
| 1.141         | 0.3401 | 52   | 1.1748          |
| 1.118         | 0.3663 | 56   | 1.1625          |
| 1.1186        | 0.3925 | 60   | 1.1571          |
| 1.1766        | 0.4186 | 64   | 1.1620          |
| 1.0801        | 0.4448 | 68   | 1.1534          |
| 1.0816        | 0.4710 | 72   | 1.1579          |
| 1.087         | 0.4971 | 76   | 1.1575          |
| 1.1822        | 0.5233 | 80   | 1.1619          |
| 1.0812        | 0.5495 | 84   | 1.1607          |
| 1.1626        | 0.5756 | 88   | 1.1611          |
| 1.21          | 0.6018 | 92   | 1.1624          |
| 1.1947        | 0.6280 | 96   | 1.1555          |
| 1.1154        | 0.6541 | 100  | 1.1518          |
| 1.1488        | 0.6803 | 104  | 1.1587          |
| 1.1402        | 0.7065 | 108  | 1.1595          |
| 1.0249        | 0.7326 | 112  | 1.1574          |
| 1.1102        | 0.7588 | 116  | 1.1472          |
| 1.1072        | 0.7850 | 120  | 1.1464          |
| 1.1382        | 0.8111 | 124  | 1.1473          |
| 1.1457        | 0.8373 | 128  | 1.1477          |
| 1.156         | 0.8635 | 132  | 1.1483          |
| 1.1037        | 0.8896 | 136  | 1.1488          |
| 1.2025        | 0.9158 | 140  | 1.1492          |
| 1.0551        | 0.9419 | 144  | 1.1496          |
| 1.0823        | 0.9681 | 148  | 1.1499          |
| 1.2344        | 0.9943 | 152  | 1.1499          |


### Framework versions

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