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gua-spa-2023-langid-ner-multilingual-bert-gn-base-cased – AI Model by jreyesp | AlphaNeural AI
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gua-spa-2023-langid-ner-multilingual-bert-gn-base-cased
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
mmaguero/multilingual-bert-gn-base-cased
finetune
mit
endpoints_compatible
us
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gua-spa-2023-langid-ner-multilingual-bert-gn-base-cased
This model is a fine-tuned version of
mmaguero/multilingual-bert-gn-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.5469
Precision: 0.1284
Recall: 0.0627
F1: 0.0843
Accuracy: 0.5285
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 OptimizerNames.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: 0.5
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
0.5
36
1.5850
0.1194
0.0548
0.0751
0.5186
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
