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NicholasCorrado/uf-tulu-2-7b-dpo-full

sourceHugging Faceupdated 2y agoView on Hugging Face
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uf-tulu-2-7b-dpo-full

This model is a fine-tuned version of models/tulu-2-7b-uf-dpo on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6557
  • —Rewards/chosen: -0.2228
  • —Rewards/rejected: -0.3409
  • —Rewards/accuracies: 0.7422
  • —Rewards/margins: 0.1181
  • —Logps/rejected: -359.4563
  • —Logps/chosen: -339.0808
  • —Logits/rejected: -1.0471
  • —Logits/chosen: -1.0577

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: 8
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 256
  • —totalevalbatch_size: 64
  • —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
0.67650.41841000.6735-0.1002-0.15500.71480.0548-340.8675-326.8218-1.1563-1.1550
0.65490.83682000.6562-0.2176-0.33420.73050.1165-358.7881-338.5682-1.0513-1.0615

Framework versions

  • —Transformers 4.44.1
  • —Pytorch 2.1.2+cu121
  • —Datasets 2.21.0
  • —Tokenizers 0.19.1