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bert-finetuned-ncbi – AI Model by Umesh | AlphaNeural AI
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Umesh
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bert-finetuned-ncbi
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
ncbi_disease
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ncbi
This model is a fine-tuned version of
bert-base-cased
on the ncbi_disease dataset. It achieves the following results on the evaluation set:
Loss: 0.0679
Precision: 0.7807
Recall: 0.8640
F1: 0.8203
Accuracy: 0.9831
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: 8
eval_batch_size: 8
seed: 42
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
0.1146
1.0
680
0.0686
0.7450
0.8056
0.7741
0.9805
0.0458
2.0
1360
0.0612
0.7646
0.8628
0.8107
0.9815
0.0161
3.0
2040
0.0679
0.7807
0.8640
0.8203
0.9831
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2
