README.md

metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - classification
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: clasificador-dair-ai
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: test
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.928

clasificador-dair-ai

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: 0.2186
• Accuracy: 0.928

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2394	1.0	2000	0.2142	0.926
0.142	2.0	4000	0.2030	0.932
0.1015	3.0	6000	0.2186	0.928

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2