README.md

metadata

license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
  - generated_from_trainer
datasets:
  - __main__
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: absa_model_v1
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: __main__
          type: __main__
          config: local
          split: test
          args: local
        metrics:
          - name: Precision
            type: precision
            value: 0.4978690430065866
          - name: Recall
            type: recall
            value: 0.5325321176958143
          - name: F1
            type: f1
            value: 0.514617541049259
          - name: Accuracy
            type: accuracy
            value: 0.7477374784110535

absa_model_v1

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the main dataset. It achieves the following results on the evaluation set:

• Loss: 0.7541
• Precision: 0.4979
• Recall: 0.5325
• F1: 0.5146
• Accuracy: 0.7477

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.7317	1.0	5905	0.7541	0.4979	0.5325	0.5146	0.7477

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.15.0