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PubMedBERT_CRAFT_NER – AI Model by judithrosell | AlphaNeural AI
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PubMedBERT_CRAFT_NER
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
finetune
mit
autotrain_compatible
endpoints_compatible
us
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PubMedBERT_CRAFT_NER
This model is a fine-tuned version of
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1031
Precision: 0.8429
Recall: 0.8679
F1: 0.8552
Accuracy: 0.9734
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
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
347
0.1280
0.7851
0.8360
0.8097
0.9647
0.1944
2.0
695
0.1092
0.8187
0.8615
0.8395
0.9707
0.046
3.0
1041
0.1031
0.8429
0.8679
0.8552
0.9734
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0
