---
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: 7.8291

## 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: 0.0003
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.2179        | 0.0262 | 4    | 1.6151          |
| 4.1153        | 0.0523 | 8    | 11.4846         |
| 9.4045        | 0.0785 | 12   | 10.9796         |
| 8.1663        | 0.1047 | 16   | 8.2167          |
| 9.0474        | 0.1308 | 20   | 10.0032         |
| 8.4796        | 0.1570 | 24   | 8.3873          |
| 7.9286        | 0.1832 | 28   | 8.0296          |
| 7.8704        | 0.2093 | 32   | 7.9253          |
| 7.7139        | 0.2355 | 36   | 7.8579          |
| 7.9416        | 0.2617 | 40   | 7.7372          |
| 7.9342        | 0.2878 | 44   | 7.8272          |
| 7.7907        | 0.3140 | 48   | 7.8569          |
| 7.9106        | 0.3401 | 52   | 7.8776          |
| 7.8242        | 0.3663 | 56   | 7.8943          |
| 7.8321        | 0.3925 | 60   | 7.8261          |
| 7.861         | 0.4186 | 64   | 7.8201          |
| 7.9374        | 0.4448 | 68   | 7.8658          |
| 7.8396        | 0.4710 | 72   | 7.8735          |
| 7.8607        | 0.4971 | 76   | 7.8436          |
| 7.9294        | 0.5233 | 80   | 7.8951          |
| 7.9017        | 0.5495 | 84   | 7.8877          |
| 7.8512        | 0.5756 | 88   | 7.8694          |
| 7.9036        | 0.6018 | 92   | 7.8331          |
| 7.8496        | 0.6280 | 96   | 7.8269          |
| 7.8837        | 0.6541 | 100  | 7.8142          |
| 7.8718        | 0.6803 | 104  | 7.9025          |
| 7.934         | 0.7065 | 108  | 7.8767          |
| 7.8706        | 0.7326 | 112  | 7.8579          |
| 7.8889        | 0.7588 | 116  | 7.8467          |
| 7.8279        | 0.7850 | 120  | 7.7952          |
| 7.9176        | 0.8111 | 124  | 7.8180          |
| 7.8894        | 0.8373 | 128  | 7.8068          |
| 7.8625        | 0.8635 | 132  | 7.8081          |
| 7.8447        | 0.8896 | 136  | 7.8196          |
| 7.7559        | 0.9158 | 140  | 7.8307          |
| 7.8508        | 0.9419 | 144  | 7.8304          |
| 7.8058        | 0.9681 | 148  | 7.8295          |
| 7.8377        | 0.9943 | 152  | 7.8291          |


### Framework versions

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