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NER-fine-tuned-BETO-finetuned-ner – AI Model by raulgdp | AlphaNeural AI
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NER-fine-tuned-BETO-finetuned-ner
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
NazaGara/NER-fine-tuned-BETO
finetune
cc-by-4.0
autotrain_compatible
endpoints_compatible
us
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NER-fine-tuned-BETO-finetuned-ner
This model is a fine-tuned version of
NazaGara/NER-fine-tuned-BETO
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2509
Precision: 0.7185
Recall: 0.6715
F1: 0.6942
Accuracy: 0.8935
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: 4
eval_batch_size: 4
seed: 42
optimizer: Use OptimizerNames.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
0.8944
1.0
777
0.3823
0.6589
0.5547
0.6023
0.8467
0.4465
2.0
1554
0.2852
0.6810
0.6399
0.6598
0.8775
0.3745
3.0
2331
0.2509
0.7185
0.6715
0.6942
0.8935
Framework versions
Transformers 4.52.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
