README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-fine-tuned-emotions
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9335

distilbert-base-uncased-fine-tuned-emotions

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: 0.1377
• Accuracy: 0.9335
• F1 Score: 0.9338

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: 0.0002
• train_batch_size: 128
• eval_batch_size: 128
• 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 Score
0.478	1.0	125	0.1852	0.931	0.9309
0.1285	2.0	250	0.1377	0.9335	0.9338

Framework versions

• Transformers 4.17.0.dev0
• Pytorch 1.8.1+cu101
• Datasets 2.7.1
• Tokenizers 0.10.1