CoolFace
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CXL295/zephyr-7b-dpo-full

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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zephyr-7b-dpo-full

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.8483
  • —Rewards/chosen: 0.7019
  • —Rewards/rejected: -1.3716
  • —Rewards/accuracies: 0.6786
  • —Rewards/margins: 2.0734
  • —Logps/rejected: -263.1501
  • —Logps/chosen: -283.4079
  • —Logits/rejected: -2.6313
  • —Logits/chosen: -2.6617

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-07
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 128
  • —totalevalbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 1

Training results

Training LossEpochStepValidation LossRewards/chosenRewards/rejectedRewards/accuraciesRewards/marginsLogps/rejectedLogps/chosenLogits/rejectedLogits/chosen
0.94810.422000.9533-0.6644-2.66410.71631.9997-264.4427-284.7741-2.6754-2.7043
1.04990.844000.85420.5163-1.59820.67662.1145-263.3767-283.5935-2.6278-2.6586

Framework versions

  • —Transformers 4.36.2
  • —Pytorch 2.1.2+cu121
  • —Datasets 2.14.6
  • —Tokenizers 0.15.2