CoolFace
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safepaca/absolute-harmfulness-predictor-redteam

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

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safetune

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1197
  • Mse: 1.1197

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: 2e-05
  • trainbatchsize: 8
  • evalbatchsize: 4
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: constant
  • num_epochs: 1.0

Training results

Training LossEpochStepValidation LossMse
2.22030.05501.82891.8289
1.89970.11001.75161.7516
1.40820.151501.39501.3950
1.58990.22001.95901.9590
1.36330.252501.33161.3316
1.37580.293001.28601.2860
1.33390.343501.26941.2694
1.28310.394001.30481.3048
1.29280.444501.23951.2395
1.25060.495001.43151.4315
1.2040.545501.15961.1596
1.17490.596001.19951.1995
1.1340.646501.37821.3782
1.30970.697001.18671.1867
1.290.747501.20241.2024
1.15750.788001.11971.1197
1.21480.838501.19441.1944
1.15970.889001.20231.2023
1.14220.939501.15461.1546
1.07340.9810001.25931.2593

Framework versions

  • Transformers 4.30.1
  • Pytorch 2.0.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.3