---
license: mit
base_model: TheBloke/zephyr-7B-alpha-GPTQ
tags:
- generated_from_trainer
- gptq
- peft
model-index:
- name: thesa
  results: []
datasets:
- loaiabdalslam/counselchat
language:
- en
pipeline_tag: text-generation
---

# Thesa: A Therapy Chatbot 👩🏻‍⚕️

Thesa is an experimental project of a therapy chatbot trained on mental health data and fine-tuned with the Zephyr GPTQ model that uses quantization to decrease high computatinal and storage costs.

## Model description

- Model type: fine-tuned from [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on various mental health datasets
- Language(s): English
- License: MIT

## Intended uses & limitations

This model is purely experimental and should not be used as substitute for a mental health professional.

## Training evaluation

Training loss:
<img src="imgs/loss_27.2.24.png" alt="loss" width="550"/>

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- warmup_ratio: 0.1
- train_batch_size: 8
- eval_batch_size: 8
- gradient_accumulation_steps: 1
- seed: 35
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
- fp16: True

Learning rate overtime (warm up ratio was used during training):
<img src="imgs/lr_27.2.24.png" alt="lr" width="550"/>

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Accelerate 0.27.2
- PEFT 0.8.2
- Auto-GPTQ 0.6.0
- TRL 0.7.11
- Optimum 1.17.1
- Bitsandbytes 0.42.0