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bert-finetuned-ner – AI Model by Stocck | AlphaNeural AI
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Stocck
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
BAAI/bge-small-en-v1.5
finetune
mit
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
BAAI/bge-small-en-v1.5
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2514
Precision: 0.8316
Recall: 0.8815
F1: 0.8558
Accuracy: 0.9729
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.4809
1.0
625
0.3984
0.7107
0.7609
0.7349
0.9543
0.2915
2.0
1250
0.2752
0.8198
0.8645
0.8416
0.9712
0.2966
3.0
1875
0.2514
0.8316
0.8815
0.8558
0.9729
Framework versions
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
