---
license: apache-2.0
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
tags:
- generated_from_trainer
model-index:
- name: healphy-GPT
  results: []
library_name: peft
---

<!-- 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. -->

# healphy-GPT

This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6624

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.GPTQ
- bits: 4
- tokenizer: None
- dataset: None
- group_size: 128
- damp_percent: 0.1
- desc_act: True
- sym: True
- true_sequential: True
- use_cuda_fp16: False
- model_seqlen: None
- block_name_to_quantize: None
- module_name_preceding_first_block: None
- batch_size: 1
- pad_token_id: None
- use_exllama: True
- max_input_length: None
- exllama_config: {'version': <ExllamaVersion.ONE: 1>}
- cache_block_outputs: True
- modules_in_block_to_quantize: None
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7738        | 0.98  | 31   | 1.4461          |
| 1.2438        | 1.98  | 63   | 1.2734          |
| 1.1119        | 2.99  | 95   | 1.1583          |
| 0.9848        | 4.0   | 127  | 1.0587          |
| 0.9112        | 4.98  | 158  | 0.9546          |
| 0.7821        | 5.98  | 190  | 0.8569          |
| 0.6926        | 6.99  | 222  | 0.7727          |
| 0.623         | 8.0   | 254  | 0.7120          |
| 0.5934        | 8.98  | 285  | 0.6737          |
| 0.5381        | 9.76  | 310  | 0.6624          |


### Framework versions

- PEFT 0.5.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.15.2