punctuation-tedtalk2012-bert-base-full-text-bert

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the tiagoblima/punctuation-tedtalk2012-full-text-bert dataset. It achieves the following results on the evaluation set:

• Loss: 0.1495
• Precision: 0.7179
• Recall: 0.7416
• F1: 0.7295
• Accuracy: 0.9417

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: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	197	0.1495	0.7179	0.7416	0.7295	0.9417

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2