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medical-multilabel-model – AI Model by sonquy | AlphaNeural AI
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sonquy
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medical-multilabel-model
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-multilingual-cased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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medical-multilabel-model
This model is a fine-tuned version of
distilbert-base-multilingual-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0130
F1 Micro: 0.9902
F1 Macro: 0.7392
Precision: 0.9910
Recall: 0.9894
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: 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: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1 Micro
F1 Macro
Precision
Recall
0.0238
1.0
945
0.0184
0.9868
0.7384
0.9878
0.9857
0.0146
2.0
1890
0.0136
0.9902
0.7387
0.9910
0.9894
0.0062
3.0
2835
0.0130
0.9902
0.7392
0.9910
0.9894
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu128
Datasets 4.0.0
Tokenizers 0.22.1
