metadata

license: mit
base_model: TheBloke/zephyr-7B-alpha-GPTQ
tags:
  - trl
  - sft
  - generated_from_trainer
  - peft
  - gptq
model-index:
  - name: thesa
    results: []
language:
  - en
datasets:
  - loaiabdalslam/counselchat
pipeline_tag: text-generation
widget:
  - text: >-
      <|system|>You are a therapist helping patients.<|user|>I'm fighting with
      my boyfriend and he's not talking to me. I don't know what to
      do<|assistant|>
    example_title: Example 1

Thesa

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

Fine-tuned from TheBloke/zephyr-7B-alpha-GPTQ

Intended uses & limitations

The intended use is experimental.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
training_steps: 250
mixed_precision_training: Native AMP

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

More info

More info at https://github.com/johnhandleyd/thesa