README.md

metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value:
              accuracy: 0.9385

bert-base-uncased-finetuned-emotion

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

• Loss: 0.1772
• Accuracy: {'accuracy': 0.9385}

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2449	1.0	1000	0.1787	{'accuracy': 0.9355}
0.1425	2.0	2000	0.1780	{'accuracy': 0.9355}
0.092	3.0	3000	0.1772	{'accuracy': 0.9385}

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3