BETO-conll2002-ner – AI Model by raulgdp | AlphaNeural AI

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raulgdp/
BETO-conll2002-ner

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token-classification

generated_from_trainer

xlnet/xlnet-large-cased

endpoints_compatible

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BETO-conll2002-ner

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

Loss: 0.1143
Precision: 0.8508
Recall: 0.8594
F1: 0.8551
Accuracy: 0.9786

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: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1225	1.0	261	0.1025	0.7819	0.8165	0.7988	0.9728
0.0634	2.0	522	0.0930	0.8201	0.8397	0.8298	0.9759
0.048	3.0	783	0.0902	0.8488	0.8533	0.8511	0.9779
0.0299	4.0	1044	0.1009	0.8431	0.8509	0.8470	0.9782
0.0197	5.0	1305	0.1054	0.8498	0.8583	0.8540	0.9791
0.0143	6.0	1566	0.1143	0.8508	0.8594	0.8551	0.9786

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1