README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
  - f1
model_index:
  - name: distilbert-base-uncased-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metric:
          name: F1
          type: f1
          value: 0.9327347950817506
model-index:
  - name: jsoutherland/distilbert-base-uncased-finetuned-emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - type: accuracy
            value: 0.925
            name: Accuracy
            verified: true
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          - type: precision
            value: 0.8954208010579672
            name: Precision Macro
            verified: true
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          - type: precision
            value: 0.925
            name: Precision Micro
            verified: true
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          - type: precision
            value: 0.9256567173431012
            name: Precision Weighted
            verified: true
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          - type: recall
            value: 0.8711059962680445
            name: Recall Macro
            verified: true
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          - type: recall
            value: 0.925
            name: Recall Micro
            verified: true
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          - type: recall
            value: 0.925
            name: Recall Weighted
            verified: true
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          - type: f1
            value: 0.8794773714607985
            name: F1 Macro
            verified: true
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          - type: f1
            value: 0.925
            name: F1 Micro
            verified: true
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          - type: f1
            value: 0.9244781949774824
            name: F1 Weighted
            verified: true
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          - type: loss
            value: 0.17752596735954285
            name: loss
            verified: true
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distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.1649
• Accuracy: 0.9325
• F1: 0.9327

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	250	0.2838	0.9065	0.9036
No log	2.0	500	0.1795	0.9255	0.9255
No log	3.0	750	0.1649	0.9325	0.9327

Framework versions

• Transformers 4.8.2
• Pytorch 1.9.0+cu102
• Datasets 2.1.0
• Tokenizers 0.10.3