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bellge/f1_score_model

sourceHugging Facemitupdated 2y agoView on Hugging Face
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f1scoremodel

This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6087
  • —Accuracy: 0.7016
  • —F1: 0.6217
  • —Precision: 0.5813
  • —Recall: 0.7016

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-05
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 100
  • —num_epochs: 5
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.42364.9810000.60870.70160.62170.58130.7016

Framework versions

  • —Transformers 4.39.3
  • —Pytorch 2.1.2
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2