README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emo
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emo
          type: emo
          config: emo2019
          split: train
          args: emo2019
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.870756943183881
          - name: F1
            type: f1
            value: 0.882390688900436

distilbert-base-uncased-finetuned-emotion

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

• Loss: 0.3616
• Accuracy: 0.8708
• F1: 0.8824

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
0.4841	1.0	472	0.3516	0.8695	0.8812
0.2767	2.0	944	0.3616	0.8708	0.8824

Framework versions

• Transformers 4.21.3
• Pytorch 1.13.1
• Datasets 2.8.0
• Tokenizers 0.12.1