peft tensorboard safetensors trl sft generated_from_trainer dataset:generator base_model:mistralai/Mistral-7B-Instruct-v0.1 base_model:adapter:mistralai/Mistral-7B-Instruct-v0.1 license:apache-2.0 region:us
---
base_model: mistralai/Mistral-7B-Instruct-v0.1
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.1_Emotion
  results: []
---

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# Mistral-7B-v0.1_McGill-MEDAL

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/@frankmorales_91352/fine-tuning-mistral-7b-instruct-v0-1-88b27a194248

Fine-tuning: https://github.com/frank-morales2020/MLxDL/blob/main/FineTuning_Mistral_7b_hfdeployment_dataset_McGill_NLP_medal.ipynb


## Intended uses & limitations

More information needed

## Training and evaluation data

Evaluation: https://github.com/frank-morales2020/MLxDL/blob/main/Mistral_7B_v0_1_McGill_MEDAL_EVALUATOR.ipynb

The following hyperparameters were used during training: 
learning_rate: 0.0002 train_batch_size: 3 eval_batch_size: 8 seed: 42 
gradient_accumulation_steps: 2 total_train_batch_size: 6 
optimizer: Adam with betas=(0.9,0.999) 
and epsilon=1e-08 lr_scheduler_type: constant lr_scheduler_warmup_ratio: 0.03 



## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 20

### Training results



### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1