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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: bertweet-base-finetuned-SARC-combined-DS
    results: []

bertweet-base-finetuned-SARC-combined-DS

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

  • Loss: 1.4624
  • Accuracy: 0.7611
  • Precision: 0.7611
  • Recall: 0.7611
  • F1: 0.7611

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 16
  • seed: 43
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.4319 4.0 44819 0.5049 0.7790 0.7796 0.7789 0.7789
0.2835 8.0 89638 0.6475 0.7663 0.7664 0.7663 0.7663
0.1797 12.0 134457 0.8746 0.7638 0.7639 0.7637 0.7637
0.1219 16.0 179276 1.0595 0.7585 0.7597 0.7587 0.7583
0.0905 20.0 224095 1.2115 0.7611 0.7612 0.7612 0.7611
0.0728 24.0 268914 1.3644 0.7628 0.7629 0.7627 0.7627
0.0612 28.0 313733 1.4624 0.7611 0.7611 0.7611 0.7611

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.3.2
  • Tokenizers 0.12.1