Gemma-2-9B-It-SAA

This model is a fine-tuned version of google/gemma-2-9b-it on the bct_non_cot_dpo_1000 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2066
  • Rewards/chosen: -0.0162
  • Rewards/rejected: -0.0908
  • Rewards/accuracies: 0.8300
  • Rewards/margins: 0.0746
  • Logps/rejected: -0.9081
  • Logps/chosen: -0.1623
  • Logits/rejected: 0.1790
  • Logits/chosen: -0.2699
  • Sft Loss: 0.0178
  • Odds Ratio Loss: 1.8881

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_ratio: 0.1
  • num_epochs: 3.0

Training results

Framework versions

  • PEFT 0.12.0
  • Transformers 4.45.2
  • Pytorch 2.3.0
  • Datasets 2.19.0
  • Tokenizers 0.20.0
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