---
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-ultrafeedback-lora
  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-ultrafeedback-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: 0.6537
- Rewards/chosen: -0.2570
- Rewards/rejected: -0.3767
- Rewards/accuracies: 0.6580
- Rewards/margins: 0.1196
- Logps/rejected: -269.1014
- Logps/chosen: -285.9487
- Logits/rejected: 0.7335
- Logits/chosen: 0.6309

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6929        | 0.21  | 100  | 0.6928          | 0.0002         | -0.0010          | 0.5320             | 0.0012          | -231.5360      | -260.2240    | 0.9168          | 0.8145        |
| 0.6893        | 0.42  | 200  | 0.6891          | -0.0038        | -0.0134          | 0.6500             | 0.0096          | -232.7742      | -260.6225    | 0.9234          | 0.8205        |
| 0.6809        | 0.63  | 300  | 0.6810          | -0.0312        | -0.0611          | 0.6680             | 0.0299          | -237.5431      | -263.3647    | 0.9151          | 0.8092        |
| 0.6671        | 0.84  | 400  | 0.6723          | -0.0854        | -0.1408          | 0.6640             | 0.0553          | -245.5124      | -268.7867    | 0.8790          | 0.7713        |
| 0.6627        | 1.05  | 500  | 0.6645          | -0.1494        | -0.2293          | 0.6680             | 0.0799          | -254.3704      | -275.1849    | 0.8294          | 0.7217        |
| 0.6476        | 1.26  | 600  | 0.6591          | -0.1979        | -0.2968          | 0.6640             | 0.0989          | -261.1124      | -280.0337    | 0.7883          | 0.6828        |
| 0.6488        | 1.47  | 700  | 0.6559          | -0.2310        | -0.3414          | 0.6620             | 0.1104          | -265.5783      | -283.3440    | 0.7549          | 0.6511        |
| 0.6449        | 1.67  | 800  | 0.6542          | -0.2518        | -0.3695          | 0.6560             | 0.1177          | -268.3814      | -285.4226    | 0.7372          | 0.6347        |
| 0.6487        | 1.88  | 900  | 0.6539          | -0.2571        | -0.3764          | 0.6560             | 0.1193          | -269.0724      | -285.9532    | 0.7320          | 0.6299        |


### Framework versions

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