---
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: openhermes-mistral-dpo-gptq
  results: []
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/eslavathvijay63-central-university-of-karnataka/huggingface/runs/2pfbrq3x)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/eslavathvijay63-central-university-of-karnataka/huggingface/runs/2pfbrq3x)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/eslavathvijay63-central-university-of-karnataka/huggingface/runs/2pfbrq3x)
# openhermes-mistral-dpo-gptq

This model is a fine-tuned version of [TheBloke/OpenHermes-2-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2-Mistral-7B-GPTQ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0           | 0.0056 | 10   | nan             |
| 0.0           | 0.0112 | 20   | nan             |
| 0.0           | 0.0169 | 30   | nan             |
| 0.0           | 0.0225 | 40   | nan             |
| 0.0           | 0.0281 | 50   | nan             |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.3
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1