---
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: 1.1146

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1799        | 0.0262 | 4    | 1.1888          |
| 1.1193        | 0.0523 | 8    | 1.1757          |
| 1.1603        | 0.0785 | 12   | 1.1751          |
| 1.0847        | 0.1047 | 16   | 1.1702          |
| 1.1304        | 0.1308 | 20   | 1.1674          |
| 1.042         | 0.1570 | 24   | 1.1582          |
| 1.1863        | 0.1832 | 28   | 1.1633          |
| 1.14          | 0.2093 | 32   | 1.1597          |
| 1.0763        | 0.2355 | 36   | 1.1503          |
| 1.135         | 0.2617 | 40   | 1.1458          |
| 1.1623        | 0.2878 | 44   | 1.1393          |
| 1.1173        | 0.3140 | 48   | 1.1423          |
| 1.1283        | 0.3401 | 52   | 1.1482          |
| 1.0967        | 0.3663 | 56   | 1.1356          |
| 1.1131        | 0.3925 | 60   | 1.1338          |
| 1.1613        | 0.4186 | 64   | 1.1419          |
| 1.0548        | 0.4448 | 68   | 1.1454          |
| 1.0629        | 0.4710 | 72   | 1.1320          |
| 1.0679        | 0.4971 | 76   | 1.1355          |
| 1.16          | 0.5233 | 80   | 1.1287          |
| 1.0579        | 0.5495 | 84   | 1.1295          |
| 1.1214        | 0.5756 | 88   | 1.1392          |
| 1.1681        | 0.6018 | 92   | 1.1242          |
| 1.1667        | 0.6280 | 96   | 1.1223          |
| 1.0871        | 0.6541 | 100  | 1.1221          |
| 1.1147        | 0.6803 | 104  | 1.1243          |
| 1.1075        | 0.7065 | 108  | 1.1254          |
| 0.9958        | 0.7326 | 112  | 1.1186          |
| 1.0718        | 0.7588 | 116  | 1.1085          |
| 1.0748        | 0.7850 | 120  | 1.1193          |
| 1.1082        | 0.8111 | 124  | 1.1138          |
| 1.0981        | 0.8373 | 128  | 1.1102          |
| 1.1231        | 0.8635 | 132  | 1.1133          |
| 1.0687        | 0.8896 | 136  | 1.1143          |
| 1.1568        | 0.9158 | 140  | 1.1139          |
| 1.0177        | 0.9419 | 144  | 1.1140          |
| 1.0401        | 0.9681 | 148  | 1.1145          |
| 1.1827        | 0.9943 | 152  | 1.1146          |


### Framework versions

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