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Gemma-7B-It-ORPO-SALT

This model is a fine-tuned version of google/gemma-7b-it on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets. It achieves the following results on the evaluation set:

  • Loss: 1.2657
  • Rewards/chosen: -0.1198
  • Rewards/rejected: -0.1438
  • Rewards/accuracies: 0.5700
  • Rewards/margins: 0.0239
  • Logps/rejected: -1.4377
  • Logps/chosen: -1.1983
  • Logits/rejected: 253.9599
  • Logits/chosen: 253.6037
  • Sft Loss: 1.1983
  • Odds Ratio Loss: 0.6746

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
1.374 0.8082 500 1.3436 -0.1276 -0.1503 0.5673 0.0227 -1.5033 -1.2762 249.9064 249.6123 1.2762 0.6738
1.1628 1.6165 1000 1.2833 -0.1215 -0.1446 0.5618 0.0231 -1.4461 -1.2153 253.1810 252.8272 1.2153 0.6796
1.1874 2.4247 1500 1.2657 -0.1198 -0.1438 0.5700 0.0239 -1.4377 -1.1983 253.9599 253.6037 1.1983 0.6746

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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