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sd-ner-v2 – AI Model by EMBO | AlphaNeural AI | AlphaNeural AI
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EMBO
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sd-ner-v2
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
source_data_nlp
mit
autotrain_compatible
endpoints_compatible
us
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sd-ner-v2
This model is a fine-tuned version of
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract
on the source_data_nlp dataset. It achieves the following results on the evaluation set:
Loss: 0.1551
Accuracy Score: 0.9513
Precision: 0.8030
Recall: 0.8378
F1: 0.8200
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: 0.0001
train_batch_size: 64
eval_batch_size: 256
seed: 42
optimizer: Adafactor
lr_scheduler_type: linear
num_epochs: 2.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy Score
Precision
Recall
F1
0.1082
1.0
785
0.1550
0.9493
0.7826
0.8402
0.8104
0.073
2.0
1570
0.1551
0.9513
0.8030
0.8378
0.8200
Framework versions
Transformers 4.20.0
Pytorch 1.11.0a0+bfe5ad2
Datasets 1.17.0
Tokenizers 0.12.1
