---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: dpo-selective-buffer-safeipo
  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-buffer-safeipo

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3423
- Rewards/chosen: -1.0061
- Rewards/rejected: -1.3040
- Rewards/accuracies: 0.7314
- Rewards/margins: 0.2980
- Rewards/safe Rewards: -0.9953
- Rewards/unsafe Rewards: -1.0113
- Logps/rejected: -222.8744
- Logps/chosen: -231.0451
- Logits/rejected: -0.6287
- Logits/chosen: -1.0992

## 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

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Rewards/safe Rewards | Rewards/unsafe Rewards | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------------:|:----------------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.0274        | 0.27  | 500  | 0.3731          | -1.0192        | -1.3005          | 0.7075             | 0.2813          | -1.0089              | -1.0281                | -222.5216      | -232.3561    | -0.9855         | -1.4616       |
| 0.9569        | 0.54  | 1000 | 0.3497          | -0.9136        | -1.2026          | 0.7210             | 0.2890          | -0.9006              | -0.9166                | -212.7308      | -221.7959    | -0.5821         | -1.0712       |
| 0.8619        | 0.81  | 1500 | 0.3429          | -0.9136        | -1.1772          | 0.7269             | 0.2635          | -0.9047              | -0.9192                | -210.1883      | -221.8018    | -0.7005         | -1.1466       |


### Framework versions

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