---
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_reverse
  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_reverse

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: 1.1558

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.3236        | 0.0261 | 4    | 1.3076          |
| 1.2244        | 0.0523 | 8    | 1.2947          |
| 1.5369        | 0.0784 | 12   | 1.4240          |
| 5.2765        | 0.1046 | 16   | 3.1163          |
| 3.5831        | 0.1307 | 20   | 1.7562          |
| 1.7895        | 0.1569 | 24   | 1.7124          |
| 1.914         | 0.1830 | 28   | 1.7797          |
| 2.9106        | 0.2092 | 32   | 2.3285          |
| 1.5011        | 0.2353 | 36   | 1.4598          |
| 1.4755        | 0.2614 | 40   | 1.4380          |
| 1.4568        | 0.2876 | 44   | 1.3801          |
| 1.2952        | 0.3137 | 48   | 1.3155          |
| 1.3008        | 0.3399 | 52   | 1.2782          |
| 1.2098        | 0.3660 | 56   | 1.2382          |
| 1.2073        | 0.3922 | 60   | 1.2299          |
| 1.2424        | 0.4183 | 64   | 1.2237          |
| 1.1401        | 0.4444 | 68   | 1.2220          |
| 1.1368        | 0.4706 | 72   | 1.2071          |
| 1.1203        | 0.4967 | 76   | 1.2119          |
| 1.21          | 0.5229 | 80   | 1.2026          |
| 1.12          | 0.5490 | 84   | 1.1905          |
| 1.199         | 0.5752 | 88   | 1.1893          |
| 1.2302        | 0.6013 | 92   | 1.1889          |
| 1.2382        | 0.6275 | 96   | 1.1797          |
| 1.1521        | 0.6536 | 100  | 1.1765          |
| 1.1563        | 0.6797 | 104  | 1.1728          |
| 1.1676        | 0.7059 | 108  | 1.1718          |
| 1.0429        | 0.7320 | 112  | 1.1642          |
| 1.1303        | 0.7582 | 116  | 1.1660          |
| 1.126         | 0.7843 | 120  | 1.1641          |
| 1.1603        | 0.8105 | 124  | 1.1598          |
| 1.146         | 0.8366 | 128  | 1.1587          |
| 1.1689        | 0.8627 | 132  | 1.1547          |
| 1.1046        | 0.8889 | 136  | 1.1533          |
| 1.201         | 0.9150 | 140  | 1.1565          |
| 1.0665        | 0.9412 | 144  | 1.1566          |
| 1.0795        | 0.9673 | 148  | 1.1561          |
| 1.2229        | 0.9935 | 152  | 1.1558          |


### Framework versions

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