---
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: microsoft/phi-2
model-index:
- name: output_dir
  results: []
license: mit
---

<!-- 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. -->

# output_dir

This model is a fine-tuned version of [phi_2_instruction](https://huggingface.co/huseyinatahaninan/phi-2-instruction) on the HuggingFaceH4/ultrafeedback_binarized dataset.

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results



### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1