---
license: mit
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi_3-offline-dpo-noise-0.0-42
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<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/pnu5z3m9)
# phi_3-offline-dpo-noise-0.0-42

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: 0.6938
- Rewards/chosen: -0.0001
- Rewards/rejected: -0.0001
- Rewards/accuracies: 0.5357
- Rewards/margins: 0.0000
- Logps/rejected: -395.4152
- Logps/chosen: -396.9144
- Logits/rejected: 12.8496
- Logits/chosen: 13.9987

## 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-06
- 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



### Framework versions

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