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bert-biobert – AI Model by Ironwolf1212 | AlphaNeural AI
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Ironwolf1212
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bert-biobert
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
biobert_json
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-biobert
This model is a fine-tuned version of
distilbert-base-uncased
on the biobert_json dataset. It achieves the following results on the evaluation set:
Loss: 0.1159
Precision: 0.9239
Recall: 0.9548
F1: 0.9391
Accuracy: 0.9698
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.5326
1.0
612
0.1450
0.9196
0.9350
0.9272
0.9642
0.175
2.0
1224
0.1159
0.9239
0.9548
0.9391
0.9698
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
