gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner

This model was trained from scratch on an conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0388
• Precision: 0.9360
• Recall: 0.9458
• F1: 0.9409
• Accuracy: 0.9902

Model description

It is based on distilbert-base-multilingual-cased

Intended uses & limitations

More information needed

Training and evaluation data

Training dataset: conll2003

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1653	1.0	878	0.0465	0.9267	0.9300	0.9283	0.9883
0.0322	2.0	1756	0.0404	0.9360	0.9431	0.9396	0.9897
0.0185	3.0	2634	0.0388	0.9360	0.9458	0.9409	0.9902

Framework versions

• Transformers 4.6.1
• Pytorch 1.8.1+cu101
• Datasets 1.6.2
• Tokenizers 0.10.2