---
license: mit
library_name: peft
tags:
- trl
- orpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: orpo-phi3
  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-phi3

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: 1.2224
- Rewards/chosen: -0.1152
- Rewards/rejected: -0.1838
- Rewards/accuracies: 1.0
- Rewards/margins: 0.0685
- Logps/rejected: -1.8375
- Logps/chosen: -1.1521
- Logits/rejected: -1.5266
- Logits/chosen: -0.4575
- Nll Loss: 1.1880
- Log Odds Ratio: -0.3436
- Log Odds Chosen: 0.8917

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 4.0204        | 0.24  | 3    | 1.2224          | -0.1152        | -0.1838          | 1.0                | 0.0685          | -1.8375        | -1.1521      | -1.5266         | -0.4575       | 1.1880   | -0.3436        | 0.8917          |
| 2.2028        | 0.48  | 6    | 1.2224          | -0.1152        | -0.1838          | 1.0                | 0.0685          | -1.8375        | -1.1521      | -1.5266         | -0.4575       | 1.1880   | -0.3436        | 0.8917          |
| 4.7852        | 0.72  | 9    | 1.2224          | -0.1152        | -0.1838          | 1.0                | 0.0685          | -1.8375        | -1.1521      | -1.5266         | -0.4575       | 1.1880   | -0.3436        | 0.8917          |
| 3.1295        | 0.96  | 12   | 1.2224          | -0.1152        | -0.1838          | 1.0                | 0.0685          | -1.8375        | -1.1521      | -1.5266         | -0.4575       | 1.1880   | -0.3436        | 0.8917          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1