---
license: mit
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi3-offline-dpo-lora-noise-0.0-5e-7-42
  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/9glz53vy)
# phi3-offline-dpo-lora-noise-0.0-5e-7-42

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: 0.6914
- Rewards/chosen: -0.0098
- Rewards/rejected: -0.0147
- Rewards/accuracies: 0.5913
- Rewards/margins: 0.0049
- Logps/rejected: -385.2070
- Logps/chosen: -409.5497
- Logits/rejected: 12.4993
- Logits/chosen: 14.2906

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6933        | 0.1778 | 100  | 0.6932          | 0.0002         | -0.0009          | 0.5278             | 0.0011          | -383.8265      | -408.5499    | 12.5336         | 14.3223       |
| 0.6942        | 0.3556 | 200  | 0.6928          | -0.0035        | -0.0064          | 0.6111             | 0.0029          | -384.3740      | -408.9154    | 12.5221         | 14.3092       |
| 0.6933        | 0.5333 | 300  | 0.6918          | -0.0073        | -0.0121          | 0.5794             | 0.0048          | -384.9481      | -409.3039    | 12.5135         | 14.3020       |
| 0.6928        | 0.7111 | 400  | 0.6914          | -0.0104        | -0.0142          | 0.5714             | 0.0038          | -385.1545      | -409.6051    | 12.4934         | 14.2847       |
| 0.6935        | 0.8889 | 500  | 0.6912          | -0.0101        | -0.0159          | 0.5913             | 0.0058          | -385.3226      | -409.5751    | 12.4995         | 14.2891       |


### Framework versions

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