ORPO-PHI-3 / README.md
joswin03's picture
Model save
2ec4e74 verified
metadata
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
  - trl
  - orpo
  - generated_from_trainer
model-index:
  - name: ORPO-PHI-3
    results: []

ORPO-PHI-3

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7712
  • Rewards/chosen: -0.1577
  • Rewards/rejected: -0.1527
  • Rewards/accuracies: 0.3000
  • Rewards/margins: -0.0050
  • Logps/rejected: -1.5273
  • Logps/chosen: -1.5771
  • Logits/rejected: 2.7883
  • Logits/chosen: 1.8098
  • Nll Loss: 1.6979
  • Log Odds Ratio: -0.7331
  • Log Odds Chosen: -0.0576

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: 8e-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • 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 Nll Loss Log Odds Ratio Log Odds Chosen
1.7534 0.2020 25 1.7712 -0.1577 -0.1527 0.3000 -0.0050 -1.5273 -1.5771 2.7883 1.8098 1.6979 -0.7331 -0.0576
1.9166 0.4040 50 1.7712 -0.1577 -0.1527 0.3000 -0.0050 -1.5273 -1.5771 2.7883 1.8098 1.6979 -0.7331 -0.0576
1.436 0.6061 75 1.7712 -0.1577 -0.1527 0.3000 -0.0050 -1.5273 -1.5771 2.7883 1.8098 1.6979 -0.7331 -0.0576
1.6618 0.8081 100 1.7712 -0.1577 -0.1527 0.3000 -0.0050 -1.5273 -1.5771 2.7883 1.8098 1.6979 -0.7331 -0.0576

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1