README.md

metadata

library_name: peft
tags:
  - alignment-handbook
  - generated_from_trainer
  - trl
  - dpo
base_model: DUAL-GPO/phi-2-kto-0-20-i1-merged
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: phi-2-kto-20-50-i2
    results: []

phi-2-kto-20-50-i2

This model is a fine-tuned version of DUAL-GPO/phi-2-kto-0-20-i1-merged 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-06
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• 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 4.36.2
• Pytorch 2.1.2
• Datasets 2.14.6
• Tokenizers 0.15.2