CoolFace
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PathofthePeople/TrainedSentiment

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

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TrainedSentiment

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0299
  • Accuracy: 0.9833

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: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
No log1.0380.60230.6233
No log2.0760.46430.7883
No log3.01140.41520.8233
No log4.01520.20170.93
No log5.01900.11280.9617
No log6.02280.06790.9767
No log7.02660.05480.9783
No log8.03040.04760.98
No log9.03420.04600.9817
No log10.03800.04140.9833
No log11.04180.04140.9817
No log12.04560.03870.9817
No log13.04940.03770.9833
0.218814.05320.03530.9833
0.218815.05700.03290.9833
0.218816.06080.03140.985
0.218817.06460.03080.985
0.218818.06840.03000.985
0.218819.07220.02970.985
0.218820.07600.02990.9833

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.12.0
  • Tokenizers 0.13.2