NER-fine-tuned-BETO-finetuned-ner

This model is a fine-tuned version of NazaGara/NER-fine-tuned-BETO on the biobert_json dataset. It achieves the following results on the evaluation set:

• Loss: 0.1199
• Precision: 0.9261
• Recall: 0.9508
• F1: 0.9383
• Accuracy: 0.9680

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3593	1.0	612	0.1199	0.9261	0.9508	0.9383	0.9680

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1
• Datasets 3.1.0
• Tokenizers 0.20.3