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cer_model-iii – AI Model by urbija | AlphaNeural AI
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urbija
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cer_model-iii
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
dmis-lab/biobert-base-cased-v1.1
finetune
autotrain_compatible
endpoints_compatible
us
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cer_model-iii
This model is a fine-tuned version of
dmis-lab/biobert-base-cased-v1.1
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2146
Precision: 0.9186
Recall: 0.8689
F1: 0.8931
Accuracy: 0.9355
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: 0.0002
train_batch_size: 16
eval_batch_size: 16
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
0.0124
1.0
4841
0.2169
0.9157
0.8545
0.8841
0.9272
0.0025
2.0
9682
0.2221
0.9180
0.8708
0.8938
0.9318
0.0001
3.0
14523
0.2146
0.9186
0.8689
0.8931
0.9355
Framework versions
Transformers 4.37.0
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.1
