herbert-finetuned-model1 – AI Model by Michal0607 | AlphaNeural AI

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Michal0607/
herbert-finetuned-model1

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token-classification

generated_from_trainer

pczarnik/herbert-base-ner

autotrain_compatible

endpoints_compatible

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herbert-finetuned-model1

This model is a fine-tuned version of pczarnik/herbert-base-ner on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0002
Precision: 0.9992
Recall: 0.9997
F1: 0.9995

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: 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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.0112	1.0	1043	0.0003	0.9965	0.9987	0.9976
0.0003	2.0	2086	0.0002	0.9987	0.9997	0.9992
0.0002	3.0	3129	0.0001	0.9992	0.9997	0.9995
0.0001	4.0	4172	0.0002	0.9987	0.9997	0.9992
0.0001	5.0	5215	0.0002	0.9992	0.9992	0.9992
0.0001	6.0	6258	0.0002	0.9990	0.9995	0.9992
0.0	7.0	7301	0.0002	0.9992	0.9997	0.9995
0.0	8.0	8344	0.0002	0.9992	0.9997	0.9995

Framework versions

Transformers 4.50.3
Pytorch 2.4.1
Datasets 2.21.0
Tokenizers 0.21.1