albert-large-v2_ner_conll2003 – AI Model by Gladiator | AlphaNeural AI

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Gladiator/
albert-large-v2_ner_conll2003

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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albert-large-v2_ner_conll2003

This model is a fine-tuned version of albert-large-v2 on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0584
Precision: 0.9396
Recall: 0.9451
F1: 0.9424
Accuracy: 0.9875

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
0.2034	1.0	878	0.0653	0.9114	0.9278	0.9195	0.9837
0.0561	2.0	1756	0.0602	0.9316	0.9280	0.9298	0.9845
0.0303	3.0	2634	0.0536	0.9380	0.9424	0.9402	0.9872
0.0177	4.0	3512	0.0535	0.9393	0.9456	0.9425	0.9877
0.011	5.0	4390	0.0584	0.9396	0.9451	0.9424	0.9875

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1