roberta-large_ner_wikiann – AI Model by Gladiator | AlphaNeural AI

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Gladiator/
roberta-large_ner_wikiann

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-large_ner_wikiann

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

Loss: 0.2783
Precision: 0.8463
Recall: 0.8634
F1: 0.8548
Accuracy: 0.9382

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
0.3395	1.0	1250	0.2652	0.8039	0.8308	0.8171	0.9242
0.2343	2.0	2500	0.2431	0.8354	0.8503	0.8428	0.9329
0.1721	3.0	3750	0.2315	0.8330	0.8503	0.8416	0.9352
0.1156	4.0	5000	0.2709	0.8477	0.8634	0.8554	0.9385
0.1026	5.0	6250	0.2783	0.8463	0.8634	0.8548	0.9382

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1