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ClinicalBERT_CRAFT_NER – AI Model by judithrosell | AlphaNeural AI
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judithrosell
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ClinicalBERT_CRAFT_NER
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
medicalai/ClinicalBERT
finetune
autotrain_compatible
endpoints_compatible
us
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ClinicalBERT_CRAFT_NER
This model is a fine-tuned version of
medicalai/ClinicalBERT
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1735
Precision: 0.7738
Recall: 0.7536
F1: 0.7636
Accuracy: 0.9553
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
0.1980
0.7224
0.7239
0.7232
0.9457
0.2292
2.0
695
0.1771
0.7528
0.7545
0.7537
0.9530
0.0815
3.0
1041
0.1735
0.7738
0.7536
0.7636
0.9553
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0
