---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral-7B-StaproCoder
  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-StaproCoder

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9444

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2899        | 0.05  | 100  | 0.2422          |
| 7.7491        | 0.1   | 200  | 6.5822          |
| 5.5972        | 0.15  | 300  | 5.4527          |
| 4.4573        | 0.2   | 400  | 4.4971          |
| 4.7321        | 0.25  | 500  | 4.5034          |
| 4.1145        | 0.3   | 600  | 4.2461          |
| 5.1351        | 0.35  | 700  | 5.2545          |
| 5.1292        | 0.4   | 800  | 4.9499          |
| 5.1284        | 0.45  | 900  | 4.9904          |
| 4.8504        | 0.5   | 1000 | 4.7120          |
| 4.7261        | 0.55  | 1100 | 4.7263          |
| 4.8442        | 0.6   | 1200 | 4.9208          |
| 4.5097        | 0.65  | 1300 | 4.3945          |
| 4.1656        | 0.7   | 1400 | 4.2131          |
| 3.7099        | 0.75  | 1500 | 4.1495          |
| 3.9017        | 0.8   | 1600 | 4.0261          |
| 4.019         | 0.85  | 1700 | 3.9943          |
| 4.0291        | 0.9   | 1800 | 3.9615          |
| 3.876         | 0.95  | 1900 | 3.9494          |
| 3.8402        | 1.0   | 2000 | 3.9444          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2