---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: dpo-selective-buffer-spo-shift
  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-spo-shift

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6777
- Rewards/chosen: -0.1371
- Rewards/rejected: -0.0830
- Rewards/accuracies: 0.4693
- Rewards/margins: -0.0541
- Rewards/safe Rewards: -0.1332
- Rewards/unsafe Rewards: -0.1263
- Logps/rejected: -92.4348
- Logps/chosen: -131.0029
- Logits/rejected: -1.8308
- Logits/chosen: -2.0825

## 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: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------------:|:----------------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 131.6857      | 0.27  | 500  | 0.8894          | -0.1023        | -0.0129          | 0.4546             | -0.0893         | -0.1043              | -0.1017                | -92.3648       | -130.9681    | -1.8032         | -2.0565       |
| 34.7958       | 0.54  | 1000 | 0.7397          | -0.1263        | -0.1290          | 0.5028             | 0.0026          | -0.1237              | -0.1264                | -92.4809       | -130.9922    | -1.7990         | -2.0551       |
| 15.9924       | 0.81  | 1500 | 0.6823          | -0.1578        | -0.1077          | 0.4713             | -0.0501         | -0.1557              | -0.1535                | -92.4596       | -131.0237    | -1.8335         | -2.0849       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2