metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: bertweet-emotion-base
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - type: accuracy
            value: 0.945
            name: Accuracy
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - type: accuracy
            value: 0.9285
            name: Accuracy
            verified: true
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          - type: precision
            value: 0.8884219402987917
            name: Precision Macro
            verified: true
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          - type: precision
            value: 0.9285
            name: Precision Micro
            verified: true
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          - type: precision
            value: 0.9294663182278102
            name: Precision Weighted
            verified: true
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          - type: recall
            value: 0.8859392810987465
            name: Recall Macro
            verified: true
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          - type: recall
            value: 0.9285
            name: Recall Micro
            verified: true
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          - type: recall
            value: 0.9285
            name: Recall Weighted
            verified: true
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          - type: f1
            value: 0.8863603878501328
            name: F1 Macro
            verified: true
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          - type: f1
            value: 0.9285
            name: F1 Micro
            verified: true
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          - type: f1
            value: 0.9284728367890772
            name: F1 Weighted
            verified: true
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          - type: loss
            value: 0.1349370777606964
            name: loss
            verified: true
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bertweet-emotion-base

This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
Loss: 0.1172
Accuracy: 0.945
Training hyperparameters

The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 80
eval_batch_size: 80
lr_scheduler_type: linear
num_epochs: 6.0
Framework versions

Transformers 4.12.5
Pytorch 1.10.0+cu113
Datasets 1.15.1
Tokenizers 0.10.3