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Medical-NER-2026-Success – AI Model by sohaibdevv | AlphaNeural AI
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Medical-NER-2026-Success
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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Medical-NER-2026-Success
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9188
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: 3e-05
train_batch_size: 8
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
No log
1.0
4
1.5839
1.8456
2.0
8
1.2376
1.2603
3.0
12
1.0594
0.9737
4.0
16
0.9637
0.8411
5.0
20
0.9188
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cpu
Datasets 4.8.3
Tokenizers 0.22.2
