bert_ftbasic_ner_model2 – AI Model by yumcoco | AlphaNeural AI

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yumcoco/
bert_ftbasic_ner_model2

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token-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert_ftbasic_ner_model2

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1803
Precision: 0.5855
Recall: 0.6524
F1: 0.6171
Accuracy: 0.9549
Macro F1: 0.5403
Micro F1: 0.9549

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: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Macro F1	Micro F1
No log	1.0	249	0.2213	0.4922	0.6235	0.5501	0.9396	0.4867	0.9396
No log	2.0	498	0.2148	0.5646	0.6104	0.5866	0.9465	0.5458	0.9465
0.2062	3.0	747	0.2274	0.5304	0.6440	0.5817	0.9436	0.5540	0.9436

Framework versions

Transformers 4.46.1
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.20.1