---
library_name: transformers
license: cc-by-nc-4.0
base_model: CohereForAI/aya-23-8B
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- simonycl/aya-23-8B_advprompter_jailbreak
model-index:
- name: aya-advprompter
  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. -->

# aya-advprompter

This model is a fine-tuned version of [CohereForAI/aya-23-8B](https://huggingface.co/CohereForAI/aya-23-8B) on the simonycl/aya-23-8B_advprompter_jailbreak dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0459
- Rewards/chosen: 0.0182
- Rewards/rejected: -6.7884
- Rewards/accuracies: 1.0
- Rewards/margins: 6.8065
- Logps/rejected: -867.2261
- Logps/chosen: -114.6688
- Logits/rejected: 0.0796
- Logits/chosen: -0.2307

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.5229        | 0.3612 | 30   | -0.4619       | -0.3434         | -98.2886     | -212.0101      | 0.5059          | 1.0                | 0.1820         | 0.4182          | -0.2362          |
| 0.2411        | 0.7223 | 60   | -0.4067       | -0.2327         | -88.9001     | -330.7860      | 0.2135          | 1.0                | 0.2758         | 1.6998          | -1.4240          |
| 0.0634        | 1.0835 | 90   | -0.2580       | -0.0357         | -99.5121     | -607.3592      | 0.0751          | 1.0                | 0.1697         | 4.3594          | -4.1897          |
| 0.0452        | 1.4454 | 120  | 0.0532        | 0.0757          | -5.9396      | 1.0            | 6.0153          | -782.3494          | -108.9159      | 0.0380          | -0.2345          |
| 0.0307        | 1.8066 | 150  | 0.0459        | 0.0182          | -6.7884      | 1.0            | 6.8065          | -867.2261          | -114.6688      | 0.0796          | -0.2307          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1