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metadata
license: mit
base_model: roberta-large
tags:
  - generated_from_trainer
datasets:
  - open_question_type
metrics:
  - f1
model-index:
  - name: roberta-large-question-classifier
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: open_question_type
          type: open_question_type
          config: default
          split: validation
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.7954091951908298

roberta-large-question-classifier

This model is a fine-tuned version of roberta-large on the open_question_type dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9002
  • F1: 0.7954

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: 512
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss F1
1.9467 1.0 233 1.3099 0.4050
0.6381 2.0 466 0.5586 0.7785
0.628 3.0 699 0.6419 0.7831
0.4487 4.0 932 0.5770 0.8094
0.3319 5.0 1165 0.7713 0.7953
0.2095 6.0 1398 0.8799 0.8018
0.1355 7.0 1631 1.0646 0.7961
0.0956 8.0 1864 1.2175 0.7999
0.0687 9.0 2097 1.3647 0.7892
0.0371 10.0 2330 1.3809 0.7987
0.0303 11.0 2563 1.3591 0.8123
0.0263 12.0 2796 1.5317 0.8100
0.0144 13.0 3029 1.5726 0.7959
0.0436 14.0 3262 1.6160 0.7988
0.0048 15.0 3495 1.6826 0.7957
0.0001 16.0 3728 1.6913 0.7957
0.0001 17.0 3961 1.7076 0.7995
0.0034 18.0 4194 1.8018 0.7960
0.0228 19.0 4427 1.7457 0.7916
0.0083 20.0 4660 1.9279 0.7869
0.0001 21.0 4893 1.8367 0.7915
0.0003 22.0 5126 1.8620 0.7842
0.0002 23.0 5359 1.9192 0.7828
0.0 24.0 5592 1.9081 0.7927
0.0003 25.0 5825 1.9822 0.7813
0.0059 26.0 6058 1.8737 0.7954
0.0 27.0 6291 1.8793 0.7929
0.0 28.0 6524 1.8905 0.7940
0.0 29.0 6757 1.8971 0.7940
0.0002 30.0 6990 1.9002 0.7954

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3