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
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.937
          - name: F1
            type: f1
            value: 0.9372331942198677
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.924
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.8811256547088461
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.924
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.9250809835160841
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.8882276452967225
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.924
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.924
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.8844059421244559
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.924
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.9243911585312775
            verified: true
          - name: loss
            type: loss
            value: 0.15944455564022064
            verified: true

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: 0.1413
• Accuracy: 0.937
• F1: 0.9372

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7628	1.0	250	0.2489	0.9155	0.9141
0.2014	2.0	500	0.1716	0.928	0.9283
0.1351	3.0	750	0.1456	0.937	0.9374
0.1046	4.0	1000	0.1440	0.9355	0.9349
0.0877	5.0	1250	0.1413	0.937	0.9372

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1