favs_token_classification_v2

This model is a fine-tuned version of bert-base-cased on the token_classification_v2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5498
• Precision: 0.6610
• Recall: 0.8417
• F1: 0.7405
• Accuracy: 0.8575

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: 1.5e-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: 20

Training results

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1
• Datasets 2.4.0
• Tokenizers 0.12.1