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taicheng/zephyr-7b-align-scan-0.0-0.4-polynomial-2

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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zephyr-7b-align-scan-0.0-0.4-polynomial-2

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: 0.8224
  • —Rewards/chosen: -0.8205
  • —Rewards/rejected: -1.9403
  • —Rewards/accuracies: 0.3433
  • —Rewards/margins: 1.1198
  • —Logps/rejected: -85.6178
  • —Logps/chosen: -76.3898
  • —Logits/rejected: -2.4242
  • —Logits/chosen: -2.4424

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: 8.772160997458124e-07
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 64
  • —totalevalbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: polynomial
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 2

Training results

Training LossEpochStepValidation LossRewards/chosenRewards/rejectedRewards/accuraciesRewards/marginsLogps/rejectedLogps/chosenLogits/rejectedLogits/chosen
0.57751.04171000.77120.75560.13330.33130.6223-80.8200-72.7430-2.5200-2.5356

Framework versions

  • —Transformers 4.44.2
  • —Pytorch 2.4.0
  • —Datasets 2.21.0
  • —Tokenizers 0.19.1