bert-base-cased_LeNER-Br

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

bert-base-cased_LeNER-Br

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

• Loss: nan
• Precision: 0.6604
• Recall: 0.7771
• F1: 0.7140
• Accuracy: 0.9648

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: 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: 10

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1

Testing results

metrics={'test_loss': 0.11072904616594315, 'test_precision': 0.7897691827822833, 'test_recall': 0.8423153692614771, 'test_f1': 0.8151963940759821, 'test_accuracy': 0.9825182903350019, 'test_runtime': 18.686, 'test_samples_per_second': 74.387, 'test_steps_per_second': 9.312})