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doplhin-mistral-dpo-ultrafeedback-binarized-preferences-kto_pair

This model is a fine-tuned version of cognitivecomputations/dolphin-2.1-mistral-7b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2024
  • Rewards/chosen: 3.9237
  • Rewards/rejected: -1.2199
  • Rewards/accuracies: 0.7871
  • Rewards/margins: 5.1437
  • Logps/rejected: -319.8331
  • Logps/chosen: -311.9210
  • Logits/rejected: -2.2827
  • Logits/chosen: -2.4135

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-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • 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
0.2261 0.25 700 0.2691 3.8384 0.5201 0.6951 3.3183 -302.4326 -312.7741 -2.4004 -2.5103
0.1934 0.51 1400 0.2197 3.0918 -2.0543 0.7802 5.1461 -328.1768 -320.2403 -2.3140 -2.4316
0.2163 0.76 2100 0.2024 3.9237 -1.2199 0.7871 5.1437 -319.8331 -311.9210 -2.2827 -2.4135

Framework versions

  • PEFT 0.8.2
  • Transformers 4.37.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.2
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