---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.1
datasets:
- generator
model-index:
- name: Mistral-7B-v0.1_AviationQA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-v0.1_AviationQA

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset.

## Model description

Article: https://medium.com/ai-in-plain-english/fine-tuning-the-mistral-7b-instruct-v0-1-model-with-aviationqa-dataset-06773d447c03

Fine Tunning Notebook: https://github.com/frank-morales2020/MLxDL/blob/main/FineTuning_Mistral_7b_hfdeployment_dataset_AviationQA.ipynb



## Intended uses & limitations

More information needed

## Training and evaluation data

Accuracy (Eval dataset and predict) for a sample of 1000: 31.00%

Evaluation Notebook: https://github.com/frank-morales2020/MLxDL/blob/main/FineTunning_Testing_For_AviationQADataset_.ipynb


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 40

### Training results



### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1