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metadata
license: mit
library_name: peft
tags:
  - trl
  - dpo
  - generated_from_trainer
base_model: google/gemma-2b
model-index:
  - name: gemma-7b-lora-distilabel-intel-orca-dpo-pairs
    results: []

gemma-7b-lora-distilabel-intel-orca-dpo-pairs

This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4641
  • Rewards/chosen: -0.2842
  • Rewards/rejected: -2.0677
  • Rewards/accuracies: 0.8414
  • Rewards/margins: 1.7835
  • Logps/rejected: -294.6812
  • Logps/chosen: -246.1420
  • Logits/rejected: -29.7875
  • Logits/chosen: -27.6122

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: 1e-05
  • 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: 250
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6333 0.19 250 0.5221 -0.4649 -1.1235 0.8196 0.6586 -285.2397 -247.9492 -29.5102 -27.3832
0.4697 0.39 500 0.4819 -0.5572 -2.0261 0.8394 1.4689 -294.2652 -248.8721 -29.5979 -27.4182
0.4471 0.58 750 0.4814 -0.5104 -2.3183 0.8418 1.8079 -297.1878 -248.4040 -29.6888 -27.5182
0.4477 0.78 1000 0.4744 -0.3874 -2.2429 0.8418 1.8555 -296.4334 -247.1736 -29.7387 -27.5680
0.458 0.97 1250 0.4641 -0.2842 -2.0677 0.8414 1.7835 -294.6812 -246.1420 -29.7875 -27.6122

Framework versions

  • PEFT 0.8.2
  • Transformers 4.38.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2