---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: phi-2-dpo-test-iter-0
  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-dpo-test-iter-0

This model is a fine-tuned version of [lole25/phi-2-sft-ultrachat-lora](https://huggingface.co/lole25/phi-2-sft-ultrachat-lora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Rewards/chosen: -0.0029
- Rewards/rejected: -0.0032
- Rewards/accuracies: 0.5130
- Rewards/margins: 0.0003
- Logps/rejected: -233.8547
- Logps/chosen: -256.9005
- Logits/rejected: 0.8721
- Logits/chosen: 0.8145

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0001        | 0.32  | 100  | 0.0002          | -0.0012        | -0.0015          | 0.5200             | 0.0003          | -233.6874      | -256.7341    | 0.8840          | 0.8263        |
| 0.0001        | 0.64  | 200  | 0.0002          | -0.0021        | -0.0023          | 0.5005             | 0.0002          | -233.7691      | -256.8278    | 0.8778          | 0.8201        |
| 0.0001        | 0.96  | 300  | 0.0002          | -0.0021        | -0.0024          | 0.4985             | 0.0003          | -233.7780      | -256.8272    | 0.8783          | 0.8206        |
| 0.0001        | 1.28  | 400  | 0.0002          | -0.0026        | -0.0029          | 0.5195             | 0.0003          | -233.8277      | -256.8757    | 0.8769          | 0.8192        |
| 0.0001        | 1.6   | 500  | 0.0002          | -0.0027        | -0.0030          | 0.5170             | 0.0003          | -233.8388      | -256.8869    | 0.8729          | 0.8151        |
| 0.0001        | 1.92  | 600  | 0.0002          | -0.0027        | -0.0030          | 0.5070             | 0.0003          | -233.8414      | -256.8860    | 0.8757          | 0.8180        |
| 0.0001        | 2.24  | 700  | 0.0002          | -0.0030        | -0.0032          | 0.5065             | 0.0002          | -233.8592      | -256.9123    | 0.8719          | 0.8142        |
| 0.0001        | 2.56  | 800  | 0.0002          | -0.0028        | -0.0030          | 0.5190             | 0.0003          | -233.8422      | -256.8898    | 0.8713          | 0.8135        |
| 0.0001        | 2.88  | 900  | 0.0002          | -0.0030        | -0.0031          | 0.5015             | 0.0002          | -233.8529      | -256.9111    | 0.8714          | 0.8136        |
| 0.0001        | 3.2   | 1000 | 0.0002          | -0.0029        | -0.0033          | 0.5180             | 0.0004          | -233.8666      | -256.9036    | 0.8733          | 0.8156        |
| 0.0001        | 3.52  | 1100 | 0.0002          | -0.0029        | -0.0034          | 0.5265             | 0.0005          | -233.8779      | -256.9080    | 0.8724          | 0.8145        |
| 0.0001        | 3.84  | 1200 | 0.0002          | -0.0031        | -0.0033          | 0.5045             | 0.0003          | -233.8733      | -256.9227    | 0.8705          | 0.8127        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2