---
license: apache-2.0
base_model: Open-Orca/Mistral-7B-OpenOrca
tags:
- generated_from_trainer
model-index:
- name: olivia-7b-dpo-lora-v2
  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. -->

# olivia-7b-dpo-lora-v2

This model is a fine-tuned version of [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2452
- Rewards/chosen: -0.7312
- Rewards/rejected: -2.7785
- Rewards/accuracies: 0.9132
- Rewards/margins: 2.0473
- Logps/rejected: -92.7458
- Logps/chosen: -70.4321
- Logits/rejected: -2.6590
- Logits/chosen: -2.6728

## 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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2434        | 1.0   | 109  | 0.2452          | -0.7312        | -2.7785          | 0.9132             | 2.0473          | -92.7458       | -70.4321     | -2.6590         | -2.6728       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1