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zephyr-dpo-timedial-selfgen-mix

This model is a fine-tuned version of EllieS/zephyr-dpo-timedial on the EllieS/timedial_selfgen dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0236
  • Rewards/chosen: 0.5600
  • Rewards/rejected: -3.3438
  • Rewards/accuracies: 1.0
  • Rewards/margins: 3.9038
  • Logps/rejected: -542.8434
  • Logps/chosen: -74.4535
  • Logits/rejected: -3.2030
  • Logits/chosen: -2.7110

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
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • 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 Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.039 0.35 100 0.0525 0.5119 -2.4372 1.0 2.9492 -452.1829 -79.2593 -3.2065 -2.7171
0.0106 0.7 200 0.0236 0.5600 -3.3438 1.0 3.9038 -542.8434 -74.4535 -3.2030 -2.7110

Framework versions

  • PEFT 0.7.1
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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Dataset used to train EllieS/zephyr-dpo-timedial-selfgen-mix