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venetis/electra-base-discriminator-finetuned-3d-sentiment

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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electra-base-discriminator-finetuned-3d-sentiment

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

  • —Loss: 0.5887
  • —Accuracy: 0.7873
  • —Precision: 0.7897
  • —Recall: 0.7873
  • —F1: 0.7864

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
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 6381
  • —num_epochs: 7
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.7971.015950.70750.73530.74340.73530.7357
0.53292.031900.65080.75500.76460.75500.7554
0.45973.047850.58890.77020.78030.77020.7695
0.39184.063800.58870.78730.78970.78730.7864
0.30935.079750.64120.78330.78770.78330.7836
0.21446.095700.77860.78440.79000.78440.7851
0.15077.0111650.84550.78530.79030.78530.7862

Framework versions

  • —Transformers 4.26.1
  • —Pytorch 1.13.1+cu117
  • —Datasets 2.10.1
  • —Tokenizers 0.13.3