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BioBERT-Symptom2Disease – AI Model by rchrdwllm | AlphaNeural AI
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BioBERT-Symptom2Disease
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transformers
safetensors
bert
text-classification
generated_from_trainer
dmis-lab/biobert-v1.1
finetune
text-embeddings-inference
endpoints_compatible
us
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BioBERT-Symptom2Disease
This model is a fine-tuned version of
dmis-lab/biobert-v1.1
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9704
Accuracy: 0.6364
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: 4.4346431315956026e-05
train_batch_size: 128
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.3808
1.0
3
1.3027
0.4091
1.2227
2.0
6
1.1699
0.6364
1.0889
3.0
9
1.0762
0.6591
1.0029
4.0
12
1.0024
0.6591
0.9398
5.0
15
0.9704
0.6364
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0
