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Gemma-7B-It-ORPO-SALT-HALF

This model is a fine-tuned version of google/gemma-7b-it on the dpo_mix_en and the bct_non_cot_dpo_500 datasets. It achieves the following results on the evaluation set:

  • Loss: 1.3159
  • Rewards/chosen: -0.1249
  • Rewards/rejected: -0.1471
  • Rewards/accuracies: 0.5619
  • Rewards/margins: 0.0222
  • Logps/rejected: -1.4709
  • Logps/chosen: -1.2488
  • Logits/rejected: 253.8645
  • Logits/chosen: 253.5439
  • Sft Loss: 1.2488
  • Odds Ratio Loss: 0.6713

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen Sft Loss Odds Ratio Loss
1.422 0.8467 500 1.3896 -0.1322 -0.1546 0.5752 0.0224 -1.5459 -1.3222 250.5634 250.2739 1.3222 0.6733
1.3103 1.6935 1000 1.3313 -0.1264 -0.1489 0.5695 0.0224 -1.4886 -1.2642 253.1350 252.8147 1.2642 0.6718
1.2057 2.5402 1500 1.3159 -0.1249 -0.1471 0.5619 0.0222 -1.4709 -1.2488 253.8645 253.5439 1.2488 0.6713

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.1
  • Pytorch 2.3.0
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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