---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: dpo-selective-redteaming
  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. -->

# dpo-selective-redteaming

This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3718.4153
- Rewards/chosen: -0.4246
- Rewards/rejected: -0.4942
- Rewards/accuracies: 0.5239
- Rewards/margins: 0.0696
- Rewards/safe Rewards: -0.4398
- Rewards/unsafe Rewards: -0.4005
- Logps/rejected: -216.6940
- Logps/chosen: -198.2132
- Logits/rejected: -2.6603
- Logits/chosen: -2.6191

## 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: 5e-07
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.0