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ner-model-BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext – AI Model by TTTingB1228011 | AlphaNeural AI
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ner-model-BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
ncbi_disease
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
finetune
mit
model-index
endpoints_compatible
us
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ner-model-BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
This model is a fine-tuned version of
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
on the ncbi_disease dataset. It achieves the following results on the evaluation set:
Loss: nan
Precision: 0.8268
Recall: 0.8948
F1: 0.8594
Accuracy: 0.9848
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: 20
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
0.0465
1.0
340
0.0537
0.7949
0.8374
0.8156
0.9836
0.0320
2.0
680
0.0466
0.8232
0.8640
0.8431
0.9856
0.0182
3.0
1020
0.0541
0.8199
0.8679
0.8432
0.9854
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 2.21.0
Tokenizers 0.22.2
