---
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: 7.8283

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 4.9343        | 0.0262 | 4    | 4.5673          |
| 9.0563        | 0.0523 | 8    | 8.5844          |
| 8.1428        | 0.0785 | 12   | 10.0610         |
| 8.7401        | 0.1047 | 16   | 9.0322          |
| 8.5719        | 0.1308 | 20   | 8.2514          |
| 8.0244        | 0.1570 | 24   | 7.8997          |
| 7.9039        | 0.1832 | 28   | 7.9731          |
| 7.9369        | 0.2093 | 32   | 7.9012          |
| 7.8205        | 0.2355 | 36   | 7.8752          |
| 7.9507        | 0.2617 | 40   | 7.9134          |
| 7.915         | 0.2878 | 44   | 7.8308          |
| 7.831         | 0.3140 | 48   | 7.8336          |
| 7.8959        | 0.3401 | 52   | 7.9525          |
| 7.7961        | 0.3663 | 56   | 7.8919          |
| 7.8427        | 0.3925 | 60   | 7.8129          |
| 7.8487        | 0.4186 | 64   | 7.8477          |
| 7.8967        | 0.4448 | 68   | 7.9020          |
| 7.8156        | 0.4710 | 72   | 7.8256          |
| 7.846         | 0.4971 | 76   | 7.8840          |
| 7.9218        | 0.5233 | 80   | 7.8602          |
| 7.8865        | 0.5495 | 84   | 7.9132          |
| 7.822         | 0.5756 | 88   | 7.8519          |
| 7.9065        | 0.6018 | 92   | 7.8543          |
| 7.8396        | 0.6280 | 96   | 7.8155          |
| 7.8712        | 0.6541 | 100  | 7.8228          |
| 7.8596        | 0.6803 | 104  | 7.8771          |
| 7.9394        | 0.7065 | 108  | 7.9084          |
| 7.8879        | 0.7326 | 112  | 7.9153          |
| 7.8493        | 0.7588 | 116  | 7.8012          |
| 7.8292        | 0.7850 | 120  | 7.8120          |
| 7.9685        | 0.8111 | 124  | 7.8322          |
| 7.8764        | 0.8373 | 128  | 7.8079          |
| 7.8677        | 0.8635 | 132  | 7.8023          |
| 7.8468        | 0.8896 | 136  | 7.8377          |
| 7.752         | 0.9158 | 140  | 7.8209          |
| 7.8344        | 0.9419 | 144  | 7.8189          |
| 7.7879        | 0.9681 | 148  | 7.8257          |
| 7.8357        | 0.9943 | 152  | 7.8283          |


### Framework versions

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