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arxiv_model – AI Model by m24coffee | AlphaNeural AI
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m24coffee
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arxiv_model
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transformers
safetensors
bert
text-classification
generated_from_trainer
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
finetune
mit
autotrain_compatible
endpoints_compatible
us
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arxiv_model
This model is a fine-tuned version of
microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.3191
Accuracy: 0.4606
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: 0.0003
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Use OptimizerNames.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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.2414
1.0
1468
2.5282
0.3647
1.8278
2.0
2936
2.1141
0.4429
1.45
3.0
4404
2.1294
0.4538
1.0671
4.0
5872
2.2140
0.4576
0.7401
4.9968
7335
2.3191
0.4606
Framework versions
Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
