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: 0.9275
          - name: F1
            type: f1
            value: 0.9273822408882375
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.919
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.8882001804445858
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.919
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.9194695149914663
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.857858142469294
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.919
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.919
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.8684381937860847
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.919
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.9182406234430719
            verified: true
          - name: loss
            type: loss
            value: 0.21632428467273712
            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: 0.2237
• Accuracy: 0.9275
• F1: 0.9274

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8643	1.0	250	0.3324	0.9065	0.9025
0.2589	2.0	500	0.2237	0.9275	0.9274

Framework versions

• Transformers 4.11.3
• Pytorch 1.11.0+cu113
• Datasets 1.16.1
• Tokenizers 0.10.3