andi611/bert-base-uncased-ner-conll2003

bert-base-uncased-ner

This model is a fine-tuned version of bert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: 2.1258
• Precision: 0.0269
• Recall: 0.1379
• F1: 0.0451
• Accuracy: 0.1988

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: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	4	2.1296	0.0270	0.1389	0.0452	0.1942
No log	2.0	8	2.1258	0.0269	0.1379	0.0451	0.1988

Framework versions

• Transformers 4.8.2
• Pytorch 1.8.1+cu111
• Datasets 1.8.0
• Tokenizers 0.10.3