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NHS-BiomedNLP-BiomedBERT-hypop-512 – AI Model by NIHNCATS | AlphaNeural AI
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NHS-BiomedNLP-BiomedBERT-hypop-512
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
finetune
mit
autotrain_compatible
endpoints_compatible
us
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NHS-BiomedNLP-BiomedBERT-hypop-512
This model is a fine-tuned version of
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3839
Accuracy: 0.8269
Precision: 0.8228
Recall: 0.8237
F1: 0.8232
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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.124
1.0
397
0.4029
0.8177
0.8146
0.8129
0.8137
0.0594
2.0
794
0.4561
0.8246
0.8245
0.8161
0.8192
0.1105
3.0
1191
0.5390
0.8120
0.8119
0.8028
0.8059
Framework versions
Transformers 4.38.2
Pytorch 2.2.2+cpu
Datasets 2.18.0
Tokenizers 0.15.2
