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This model is a fine-tuned version of google/gemma-2-9b-it on the cdc0b2d9-493b-4cb1-87e8-8fb1e3f4b247 dataset. It achieves the following results on the evaluation set:

  • Loss: 3.9434
  • Rewards/chosen: -46.0543
  • Rewards/rejected: -47.7041
  • Rewards/accuracies: 0.6473
  • Rewards/margins: 1.6497
  • Logps/rejected: -4.7704
  • Logps/chosen: -4.6054
  • Logits/rejected: 14.6796
  • Logits/chosen: 14.4459

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-07
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 32
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
3.9873 1.0 7344 3.9434 -46.0543 -47.7041 0.6473 1.6497 -4.7704 -4.6054 14.6796 14.4459

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.3.0
  • Datasets 2.21.0
  • Tokenizers 0.20.2
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