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: 0.925
          - name: F1
            type: f1
            value: 0.925169929474641
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9185
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.8812304360487162
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.9185
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.9186256759712246
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.8685675449036236
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.9185
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.9185
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.8737330835692586
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.9185
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.9182854700791021
            verified: true
          - name: loss
            type: loss
            value: 0.2216690629720688
            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: 0.2202
• Accuracy: 0.925
• F1: 0.9252

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
0.8419	1.0	250	0.3236	0.9025	0.8999
0.258	2.0	500	0.2202	0.925	0.9252

Framework versions

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