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ner-bio-1 – AI Model by urbija | AlphaNeural AI
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urbija
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ner-bio-1
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transformers
pytorch
bert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ner-bio-1
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3706
Precision: 0.8569
Recall: 0.8603
F1: 0.8586
Accuracy: 0.8803
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
lr_scheduler_warmup_ratio: 0.2
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
240
0.6566
0.6683
0.7443
0.7043
0.7790
No log
2.0
480
0.4004
0.8227
0.8461
0.8342
0.8680
0.9843
3.0
720
0.3706
0.8569
0.8603
0.8586
0.8803
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cpu
Datasets 2.1.0
Tokenizers 0.13.3
