roberta-large_ner_wnut_17 – AI Model by Gladiator | AlphaNeural AI

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Gladiator/
roberta-large_ner_wnut_17

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-large_ner_wnut_17

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

Loss: 0.2288
Precision: 0.7346
Recall: 0.6256
F1: 0.6757
Accuracy: 0.9650

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	0.1805	0.6403	0.6089	0.6242	0.9598
No log	2.0	426	0.1925	0.7314	0.5993	0.6588	0.9624
0.1192	3.0	639	0.1883	0.7088	0.6172	0.6598	0.9637
0.1192	4.0	852	0.2144	0.7289	0.6400	0.6815	0.9655
0.0301	5.0	1065	0.2288	0.7346	0.6256	0.6757	0.9650

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1