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biomistral-7b-wo-kqa_golden-iter-dpo-step3

This model is a fine-tuned version of Minbyul/biomistral-7b-wo-kqa_golden-iter-dpo-step2 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6829
  • Rewards/chosen: -0.0502
  • Rewards/rejected: -0.0800
  • Rewards/accuracies: 0.6300
  • Rewards/margins: 0.0298
  • Logps/rejected: -60.1185
  • Logps/chosen: -40.1264
  • Logits/rejected: -1.5228
  • Logits/chosen: -0.8710

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-07
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • 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

Training results

Training Loss Epoch Step Logits/chosen Logits/rejected Logps/chosen Logps/rejected Validation Loss Rewards/accuracies Rewards/chosen Rewards/margins Rewards/rejected
0.6794 0.37 100 -0.8266 -1.4757 -35.5860 -53.0765 0.6906 0.5900 -0.0048 0.0048 -0.0096
0.6555 0.74 200 -0.8589 -1.5130 -39.0432 -58.7210 0.6837 0.6400 -0.0394 0.0267 -0.0661

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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Finetuned from

Dataset used to train dmis-lab/biomistral-7b-olaph