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ner-bio-annotated-5 – AI Model by urbija | AlphaNeural AI
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urbija
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ner-bio-annotated-5
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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-annotated-5
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: 0.1390
Precision: 0.7677
Recall: 0.7918
F1: 0.7796
Accuracy: 0.9661
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: 0.0003
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
67
0.1994
0.5766
0.6632
0.6169
0.9385
No log
2.0
134
0.1514
0.7274
0.7820
0.7537
0.9599
No log
3.0
201
0.1390
0.7677
0.7918
0.7796
0.9661
Framework versions
Transformers 4.30.2
Pytorch 2.0.0+cpu
Datasets 2.1.0
Tokenizers 0.13.3
