---
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-ipo-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-ipo-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: 2546.4375
- Rewards/chosen: -0.1591
- Rewards/rejected: -0.1612
- Rewards/accuracies: 0.5220
- Rewards/margins: 0.0021
- Logps/rejected: -249.6534
- Logps/chosen: -272.5227
- Logits/rejected: 0.4171
- Logits/chosen: 0.3526

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2477.3281     | 0.32  | 100  | 2500.7156       | -0.0018        | -0.0018          | 0.4930             | -0.0000         | -233.7207      | -256.7978    | 0.8796          | 0.8221        |
| 2224.3488     | 0.64  | 200  | 2499.8904       | -0.0195        | -0.0198          | 0.5015             | 0.0003          | -235.5204      | -258.5673    | 0.8051          | 0.7462        |
| 1898.0719     | 0.96  | 300  | 2505.6912       | -0.0563        | -0.0571          | 0.5140             | 0.0008          | -239.2530      | -262.2491    | 0.6844          | 0.6233        |
| 1879.8852     | 1.28  | 400  | 2516.0835       | -0.0944        | -0.0957          | 0.5200             | 0.0013          | -243.1053      | -266.0533    | 0.5839          | 0.5215        |
| 1917.2811     | 1.6   | 500  | 2527.1995       | -0.1156        | -0.1170          | 0.5115             | 0.0014          | -245.2343      | -268.1747    | 0.5244          | 0.4611        |
| 1799.3824     | 1.92  | 600  | 2534.4292       | -0.1363        | -0.1381          | 0.5210             | 0.0018          | -247.3504      | -270.2482    | 0.4714          | 0.4075        |
| 1751.5762     | 2.24  | 700  | 2531.3550       | -0.1448        | -0.1474          | 0.5180             | 0.0026          | -248.2780      | -271.0988    | 0.4545          | 0.3906        |
| 1711.1711     | 2.56  | 800  | 2536.2451       | -0.1487        | -0.1511          | 0.5145             | 0.0024          | -248.6440      | -271.4834    | 0.4402          | 0.3759        |
| 1894.4447     | 2.88  | 900  | 2542.6299       | -0.1549        | -0.1570          | 0.5235             | 0.0022          | -249.2417      | -272.1000    | 0.4262          | 0.3618        |
| 1798.5389     | 3.2   | 1000 | 2542.7288       | -0.1581        | -0.1604          | 0.5205             | 0.0023          | -249.5780      | -272.4200    | 0.4202          | 0.3559        |
| 1834.9711     | 3.52  | 1100 | 2542.2373       | -0.1586        | -0.1610          | 0.5205             | 0.0024          | -249.6345      | -272.4703    | 0.4177          | 0.3532        |
| 1765.5148     | 3.84  | 1200 | 2546.1714       | -0.1589        | -0.1610          | 0.5220             | 0.0021          | -249.6357      | -272.5010    | 0.4160          | 0.3515        |


### Framework versions

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