bert-large-uncased_ner_wnut_17 – AI Model by Gladiator | AlphaNeural AI

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Gladiator/
bert-large-uncased_ner_wnut_17

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-large-uncased_ner_wnut_17

This model is a fine-tuned version of bert-large-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:

Loss: 0.2516
Precision: 0.7053
Recall: 0.5754
F1: 0.6337
Accuracy: 0.9603

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2143	0.6353	0.4605	0.5340	0.9490
No log	2.0	426	0.2299	0.7322	0.5036	0.5967	0.9556
0.1489	3.0	639	0.2137	0.6583	0.5945	0.6248	0.9603
0.1489	4.0	852	0.2494	0.7035	0.5789	0.6352	0.9604
0.0268	5.0	1065	0.2516	0.7053	0.5754	0.6337	0.9603

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1