---
license: mit
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
  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. -->

# phi2-lora-quantized-distilabel-intel-orca-dpo-pairs

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5173
- Rewards/chosen: -0.0019
- Rewards/rejected: -0.7725
- Rewards/accuracies: 0.7816
- Rewards/margins: 0.7706
- Logps/rejected: -233.5226
- Logps/chosen: -214.1249
- Logits/rejected: 0.3181
- Logits/chosen: 0.2015

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6887        | 0.14  | 20   | 0.6767          | 0.0030         | -0.0331          | 0.6341             | 0.0361          | -226.1282      | -214.0752    | 0.2238          | 0.1343        |
| 0.6472        | 0.27  | 40   | 0.6171          | 0.0141         | -0.1710          | 0.7639             | 0.1852          | -227.5079      | -213.9642    | 0.2464          | 0.1508        |
| 0.5759        | 0.41  | 60   | 0.5584          | 0.0123         | -0.4023          | 0.7808             | 0.4146          | -229.8206      | -213.9829    | 0.2774          | 0.1736        |
| 0.526         | 0.54  | 80   | 0.5326          | 0.0036         | -0.5790          | 0.7816             | 0.5826          | -231.5877      | -214.0700    | 0.2983          | 0.1884        |
| 0.4963        | 0.68  | 100  | 0.5225          | 0.0020         | -0.6964          | 0.7825             | 0.6984          | -232.7611      | -214.0853    | 0.3131          | 0.1986        |
| 0.4977        | 0.81  | 120  | 0.5188          | -0.0025        | -0.7533          | 0.7816             | 0.7508          | -233.3300      | -214.1302    | 0.3162          | 0.2002        |
| 0.4818        | 0.95  | 140  | 0.5173          | -0.0019        | -0.7725          | 0.7816             | 0.7706          | -233.5226      | -214.1249    | 0.3181          | 0.2015        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.1
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1