---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: phi-2-gpo-renew2-b0.001-v4-i1
  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. -->

# phi-2-gpo-renew2-b0.001-v4-i1

This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-renew2-b0.001-i0](https://huggingface.co/DUAL-GPO/phi-2-gpo-renew2-b0.001-i0) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0536
- Rewards/chosen: -0.0036
- Rewards/rejected: -0.0039
- Rewards/accuracies: 0.4695
- Rewards/margins: 0.0002
- Logps/rejected: -371.0876
- Logps/chosen: -399.9150
- Logits/rejected: -0.7623
- Logits/chosen: -0.8574

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_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 | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1203        | 0.32  | 100  | 0.0537          | -0.0024        | -0.0024          | 0.4555             | 0.0001          | -369.6694      | -398.6797    | -0.7167         | -0.8167       |
| 0.1671        | 0.64  | 200  | 0.0537          | -0.0036        | -0.0037          | 0.4670             | 0.0001          | -370.9240      | -399.8586    | -0.7745         | -0.8674       |
| 0.1393        | 0.96  | 300  | 0.0536          | -0.0038        | -0.0040          | 0.4625             | 0.0003          | -371.2791      | -400.0731    | -0.7820         | -0.8772       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2