bert-large-uncased-wnut_17-full – AI Model by yefo-ufpe | AlphaNeural AI

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yefo-ufpe/
bert-large-uncased-wnut_17-full

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token-classification

generated_from_trainer

google-bert/bert-large-uncased

autotrain_compatible

endpoints_compatible

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bert-large-uncased-wnut_17-full

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

Loss: 0.4040
Precision: 0.6546
Recall: 0.3865
F1: 0.4860
Accuracy: 0.9493

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: 5e-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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2471	0.6341	0.3726	0.4694	0.9461
No log	2.0	426	0.2454	0.5882	0.3707	0.4548	0.9475
0.1196	3.0	639	0.3091	0.6278	0.3689	0.4647	0.9490
0.1196	4.0	852	0.3758	0.6536	0.3411	0.4482	0.9473
0.0235	5.0	1065	0.3127	0.5632	0.4004	0.4680	0.9490
0.0235	6.0	1278	0.3988	0.6562	0.3698	0.4730	0.9492
0.0235	7.0	1491	0.4040	0.6546	0.3865	0.4860	0.9493

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1