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bert-base-uncased-finetuned-medmcqa-2024-11-25-T14-48-41 – AI Model by maxg73872 | AlphaNeural AI
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bert-base-uncased-finetuned-medmcqa-2024-11-25-T14-48-41
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transformers
safetensors
bert
multiple-choice
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-base-uncased-finetuned-medmcqa-2024-11-25-T14-48-41
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3614
Accuracy: 0.5
F1: 0.5106
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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
1.3558
0.9978
57
1.3614
0.5
0.5106
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
