---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_magiccoder_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-v0.3_magiccoder_ortho

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.8233

## 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_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.7819        | 0.0262 | 4    | 5.1512          |
| 9.2164        | 0.0523 | 8    | 8.3377          |
| 8.1082        | 0.0785 | 12   | 8.9375          |
| 9.0762        | 0.1047 | 16   | 8.3063          |
| 8.2007        | 0.1308 | 20   | 8.0203          |
| 8.168         | 0.1570 | 24   | 8.2340          |
| 7.8692        | 0.1832 | 28   | 7.8876          |
| 7.8831        | 0.2093 | 32   | 7.8978          |
| 7.7946        | 0.2355 | 36   | 7.8117          |
| 7.8717        | 0.2617 | 40   | 7.8140          |
| 7.9497        | 0.2878 | 44   | 7.9363          |
| 8.0978        | 0.3140 | 48   | 7.9038          |
| 7.8654        | 0.3401 | 52   | 7.8165          |
| 7.8036        | 0.3663 | 56   | 7.8578          |
| 7.8264        | 0.3925 | 60   | 7.8504          |
| 7.8333        | 0.4186 | 64   | 7.8426          |
| 7.8526        | 0.4448 | 68   | 7.8285          |
| 7.802         | 0.4710 | 72   | 7.7864          |
| 7.8376        | 0.4971 | 76   | 7.8583          |
| 7.8992        | 0.5233 | 80   | 7.8449          |
| 7.8557        | 0.5495 | 84   | 7.8771          |
| 7.8194        | 0.5756 | 88   | 7.8423          |
| 7.9157        | 0.6018 | 92   | 7.8123          |
| 7.8291        | 0.6280 | 96   | 7.7872          |
| 7.8662        | 0.6541 | 100  | 7.8912          |
| 7.8973        | 0.6803 | 104  | 7.9091          |
| 7.9194        | 0.7065 | 108  | 7.9010          |
| 7.8688        | 0.7326 | 112  | 7.8714          |
| 7.8032        | 0.7588 | 116  | 7.7568          |
| 7.7982        | 0.7850 | 120  | 7.7807          |
| 7.9577        | 0.8111 | 124  | 7.8259          |
| 7.886         | 0.8373 | 128  | 7.8117          |
| 7.8537        | 0.8635 | 132  | 7.7975          |
| 7.832         | 0.8896 | 136  | 7.8116          |
| 7.7412        | 0.9158 | 140  | 7.8055          |
| 7.822         | 0.9419 | 144  | 7.8141          |
| 7.7889        | 0.9681 | 148  | 7.8214          |
| 7.8316        | 0.9943 | 152  | 7.8233          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1