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bert-finetuned-ner – AI Model by szoplakz-class | AlphaNeural AI
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szoplakz-class
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bert-finetuned-ner
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.8755
Precision: 0.0326
Recall: 0.0909
F1: 0.0480
Accuracy: 0.5776
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 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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
2
2.1029
0.0606
0.4242
0.1061
0.2759
No log
2.0
4
1.9413
0.048
0.1818
0.0759
0.5086
No log
3.0
6
1.8755
0.0326
0.0909
0.0480
0.5776
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1
