---
license: mit
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi3-offline-dpo-lora-noise-0.0-5e-7-thre-1.5-42
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/causal/huggingface/runs/3pqwimtf)
# phi3-offline-dpo-lora-noise-0.0-5e-7-thre-1.5-42

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6131
- Rewards/chosen: -0.4150
- Rewards/rejected: -0.5892
- Rewards/accuracies: 0.7540
- Rewards/margins: 0.1743
- Logps/rejected: -459.2376
- Logps/chosen: -447.7001
- Logits/rejected: 12.5314
- Logits/chosen: 13.8427

## 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-07
- 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6885        | 0.1778 | 100  | 0.6884          | -0.0158        | -0.0244          | 0.6190             | 0.0086          | -402.7496      | -407.7805    | 12.8305         | 14.2621       |
| 0.6712        | 0.3556 | 200  | 0.6680          | -0.0971        | -0.1464          | 0.7937             | 0.0493          | -414.9504      | -415.9148    | 12.6482         | 14.0845       |
| 0.6339        | 0.5333 | 300  | 0.6389          | -0.2593        | -0.3712          | 0.7540             | 0.1119          | -437.4307      | -432.1300    | 12.8556         | 14.1744       |
| 0.6203        | 0.7111 | 400  | 0.6203          | -0.3738        | -0.5313          | 0.7540             | 0.1575          | -453.4457      | -443.5887    | 12.6256         | 13.9444       |
| 0.6102        | 0.8889 | 500  | 0.6131          | -0.4150        | -0.5892          | 0.7540             | 0.1743          | -459.2376      | -447.7001    | 12.5314         | 13.8427       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1