---
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-extra-v2-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-extra-v2-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: 0.0388
- Rewards/chosen: 0.0266
- Rewards/rejected: -0.0126
- Rewards/accuracies: 0.6070
- Rewards/margins: 0.0392
- Logps/rejected: -379.8497
- Logps/chosen: -369.7509
- Logits/rejected: -0.9196
- Logits/chosen: -0.9539

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.098         | 0.06  | 100  | 0.0533          | -0.0029        | -0.0036          | 0.4980             | 0.0007          | -370.8433      | -399.2503    | -0.7225         | -0.8171       |
| 0.094         | 0.13  | 200  | 0.0491          | -0.0390        | -0.0525          | 0.5525             | 0.0135          | -419.6949      | -435.2693    | -1.0754         | -1.1388       |
| 0.0898        | 0.19  | 300  | 0.0452          | -0.0184        | -0.0403          | 0.5780             | 0.0218          | -407.5088      | -414.7480    | -1.0291         | -1.0858       |
| 0.0731        | 0.26  | 400  | 0.0430          | -0.0069        | -0.0331          | 0.5970             | 0.0262          | -400.2979      | -403.1916    | -0.9864         | -1.0412       |
| 0.0787        | 0.32  | 500  | 0.0422          | -0.0122        | -0.0473          | 0.6070             | 0.0351          | -414.4887      | -408.4566    | -1.0587         | -1.0975       |
| 0.0742        | 0.38  | 600  | 0.0406          | 0.0135         | -0.0175          | 0.6085             | 0.0309          | -384.7105      | -382.8363    | -0.9872         | -1.0246       |
| 0.0635        | 0.45  | 700  | 0.0401          | 0.0166         | -0.0188          | 0.6095             | 0.0354          | -386.0258      | -379.6696    | -0.9903         | -1.0225       |
| 0.0881        | 0.51  | 800  | 0.0395          | 0.0250         | -0.0102          | 0.6085             | 0.0352          | -377.4323      | -371.2672    | -0.9658         | -0.9975       |
| 0.0753        | 0.58  | 900  | 0.0393          | 0.0304         | -0.0046          | 0.5990             | 0.0350          | -371.7872      | -365.8699    | -0.9026         | -0.9456       |
| 0.0922        | 0.64  | 1000 | 0.0390          | 0.0286         | -0.0075          | 0.5990             | 0.0361          | -374.7669      | -367.7319    | -0.8801         | -0.9184       |
| 0.0703        | 0.7   | 1100 | 0.0389          | 0.0227         | -0.0161          | 0.6000             | 0.0387          | -383.3026      | -373.6226    | -0.9300         | -0.9602       |
| 0.0746        | 0.77  | 1200 | 0.0388          | 0.0226         | -0.0179          | 0.6050             | 0.0405          | -385.1601      | -373.7153    | -0.8944         | -0.9306       |
| 0.0925        | 0.83  | 1300 | 0.0387          | 0.0263         | -0.0131          | 0.6030             | 0.0393          | -380.3072      | -370.0340    | -0.9171         | -0.9494       |
| 0.0863        | 0.9   | 1400 | 0.0387          | 0.0269         | -0.0123          | 0.6055             | 0.0392          | -379.5608      | -369.4450    | -0.9121         | -0.9447       |
| 0.0904        | 0.96  | 1500 | 0.0386          | 0.0268         | -0.0124          | 0.6045             | 0.0392          | -379.6000      | -369.4944    | -0.9203         | -0.9536       |


### Framework versions

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