---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: ORPO-PHI-3
  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. -->

# ORPO-PHI-3

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7712
- Rewards/chosen: -0.1577
- Rewards/rejected: -0.1527
- Rewards/accuracies: 0.3000
- Rewards/margins: -0.0050
- Logps/rejected: -1.5273
- Logps/chosen: -1.5771
- Logits/rejected: 2.7883
- Logits/chosen: 1.8098
- Nll Loss: 1.6979
- Log Odds Ratio: -0.7331
- Log Odds Chosen: -0.0576

## 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: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.7534        | 0.2020 | 25   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
| 1.9166        | 0.4040 | 50   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
| 1.436         | 0.6061 | 75   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
| 1.6618        | 0.8081 | 100  | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1