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metadata
license: mit
library_name: peft
tags:
  - alignment-handbook
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
base_model: microsoft/phi-2
model-index:
  - name: phi-2-gpo-ultrachat-lora-2
    results: []

phi-2-gpo-ultrachat-lora-2

This model is a fine-tuned version of lole25/phi-2-sft-ultrachat-lora on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0093
  • Rewards/chosen: -0.0154
  • Rewards/rejected: -0.0218
  • Rewards/accuracies: 0.3500
  • Rewards/margins: 0.0064
  • Logps/rejected: -96.3794
  • Logps/chosen: -93.2678
  • Logits/rejected: 0.7520
  • Logits/chosen: 0.7332

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: 2

Training results

Training Loss Epoch Step Logits/chosen Logits/rejected Logps/chosen Logps/rejected Validation Loss Rewards/accuracies Rewards/chosen Rewards/margins Rewards/rejected
0.01 1.04 100 0.8011 0.8188 -91.7671 -94.2623 0.0100 0.25 -0.0004 0.0003 -0.0007
0.0098 0.42 200 0.0098 -0.0018 -0.0032 0.3060 0.0015 -94.5191 -91.9032 0.8107 0.7928
0.0095 0.63 300 0.0096 -0.0058 -0.0088 0.3060 0.0030 -95.0819 -92.3092 0.7982 0.7800
0.0091 0.84 400 0.0094 -0.0110 -0.0157 0.3340 0.0047 -95.7642 -92.8250 0.7753 0.7565
0.0094 1.05 500 0.0093 -0.0132 -0.0192 0.3400 0.0060 -96.1150 -93.0463 0.7679 0.7492
0.0093 1.26 600 0.0093 -0.0144 -0.0207 0.3440 0.0063 -96.2631 -93.1677 0.7578 0.7383
0.009 1.47 700 0.0093 -0.0152 -0.0212 0.3480 0.0060 -96.3198 -93.2491 0.7545 0.7355
0.009 1.67 800 0.0093 -0.0155 -0.0218 0.3420 0.0063 -96.3791 -93.2749 0.7523 0.7328
0.0091 1.88 900 0.0093 -0.0156 -0.0218 0.3480 0.0063 -96.3809 -93.2841 0.7515 0.7320

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.14.6
  • Tokenizers 0.15.2