---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: microsoft/phi-2
model-index:
- name: phi-2-dpo-ultrachat-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# phi-2-dpo-ultrachat-lora

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: 0.6912
- Rewards/chosen: -0.0072
- Rewards/rejected: -0.0111
- Rewards/accuracies: 0.3180
- Rewards/margins: 0.0040
- Logps/rejected: -95.3090
- Logps/chosen: -92.4438
- Logits/rejected: 0.8021
- Logits/chosen: 0.7828

## 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
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.693         | 0.21  | 100  | 0.6931          | -0.0005        | -0.0008          | 0.2680             | 0.0004          | -94.2804       | -91.7748     | 0.8176          | 0.7998        |
| 0.6922        | 0.42  | 200  | 0.6924          | -0.0018        | -0.0032          | 0.3020             | 0.0014          | -94.5141       | -91.9068     | 0.8121          | 0.7941        |
| 0.6917        | 0.63  | 300  | 0.6917          | -0.0049        | -0.0077          | 0.3100             | 0.0028          | -94.9659       | -92.2189     | 0.8057          | 0.7870        |
| 0.6905        | 0.84  | 400  | 0.6913          | -0.0070        | -0.0105          | 0.3280             | 0.0036          | -95.2509       | -92.4247     | 0.8012          | 0.7827        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2