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zephyr-dpo-timedial-selfgen

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

  • Loss: 0.0055
  • Rewards/chosen: 0.4843
  • Rewards/rejected: -5.0618
  • Rewards/accuracies: 1.0
  • Rewards/margins: 5.5461
  • Logps/rejected: -740.9361
  • Logps/chosen: -96.9992
  • Logits/rejected: -3.1155
  • Logits/chosen: -2.6815

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
0.0166 0.35 100 0.0198 0.4885 -3.4443 1.0 3.9328 -579.1801 -96.5815 -3.1058 -2.6808
0.0015 0.7 200 0.0055 0.4843 -5.0618 1.0 5.5461 -740.9361 -96.9992 -3.1155 -2.6815

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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