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bertweet-base-finetuned-SARC-DS

Text Classification
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PyTorch
roberta
Generated from Trainer
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
widget:
  - text: I'm ecstatic my flight was just delayed
model-index:
  - name: bertweet-base-finetuned-SARC-DS
    results: []

bertweet-base-finetuned-SARC-DS

This model is a fine-tuned version of vinai/bertweet-base on the SARC dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7094
  • Accuracy: 0.7636
  • Precision: 0.7637
  • Recall: 0.7636
  • F1: 0.7636

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: 16
  • eval_batch_size: 32
  • seed: 43
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.4978 1.0 44221 0.4899 0.7777 0.7787 0.7778 0.7775
0.4413 2.0 88442 0.4833 0.7798 0.7803 0.7798 0.7797
0.3943 3.0 132663 0.5387 0.7784 0.7784 0.7784 0.7784
0.3461 4.01 176884 0.6184 0.7690 0.7701 0.7690 0.7688
0.3024 5.01 221105 0.6899 0.7684 0.7691 0.7684 0.7682
0.2653 6.01 265326 0.7805 0.7654 0.7660 0.7654 0.7653
0.2368 7.01 309547 0.9066 0.7643 0.7648 0.7643 0.7642
0.2166 8.01 353768 1.0548 0.7612 0.7620 0.7611 0.7610
0.2005 9.01 397989 1.0649 0.7639 0.7639 0.7639 0.7639
0.1837 10.02 442210 1.1805 0.7621 0.7624 0.7621 0.7621
0.1667 11.02 486431 1.3017 0.7658 0.7659 0.7659 0.7658
0.1531 12.02 530652 1.2947 0.7627 0.7628 0.7627 0.7627
0.1377 13.02 574873 1.3877 0.7639 0.7639 0.7639 0.7639
0.1249 14.02 619094 1.4468 0.7613 0.7616 0.7613 0.7612
0.1129 15.02 663315 1.4951 0.7620 0.7621 0.7620 0.7620
0.103 16.02 707536 1.5599 0.7619 0.7624 0.7619 0.7618
0.0937 17.03 751757 1.6270 0.7615 0.7616 0.7615 0.7615
0.0864 18.03 795978 1.6918 0.7622 0.7624 0.7622 0.7621
0.0796 19.03 840199 1.7094 0.7636 0.7637 0.7636 0.7636

Framework versions

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