aomar85 / finetuned-marbert-random-dataset

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Model's Last Updated: July 31 2022
text-classification

Introduction of finetuned-marbert-random-dataset

Model Details of finetuned-marbert-random-dataset

finetuned-marbert-random-dataset

This model is a fine-tuned version of UBC-NLP/MARBERTv2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0516
  • Accuracy: 0.9934
  • Precision: 0.9999
  • Recall: 0.9869
  • F1: 0.9933
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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.0213 1.0 62920 0.0158 0.9973 0.9984 0.9961 0.9973
0.0171 2.0 125840 0.0140 0.9976 0.9968 0.9983 0.9976
0.0145 3.0 188760 0.0168 0.9977 0.9969 0.9985 0.9977
0.0087 4.0 251680 0.0166 0.9973 0.9995 0.9951 0.9973
0.0066 5.0 314600 0.0516 0.9934 0.9999 0.9869 0.9933
Framework versions
  • Transformers 4.21.0
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1

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