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BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext-finetuned-ner – AI Model by grazh | AlphaNeural AI
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BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext-finetuned-ner
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transformers
tensorboard
onnx
safetensors
bert
token-classification
generated_from_trainer
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
quantized
mit
endpoints_compatible
us
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BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext-finetuned-ner
This model is a fine-tuned version of
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1194
Precision: 0.7245
Recall: 0.8681
F1: 0.7898
Accuracy: 0.9547
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
No log
1.0
364
0.1323
0.6965
0.8613
0.7702
0.9515
0.212
2.0
728
0.1168
0.7195
0.8646
0.7854
0.9538
0.1015
3.0
1092
0.1194
0.7245
0.8681
0.7898
0.9547
Framework versions
Transformers 4.57.1
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1
