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ModernBERT-domain-classifier – AI Model by AnhNam | AlphaNeural AI
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AnhNam
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ModernBERT-domain-classifier
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transformers
safetensors
modernbert
text-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ModernBERT-domain-classifier
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5256
Accuracy: 0.9409
Precision: 1.0
Recall: 0.9409
F1: 0.9696
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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Use 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
Accuracy
Precision
Recall
F1
5.1956
0.8727
6
0.5418
0.9273
1.0
0.9273
0.9623
5.6924
1.8727
12
0.5299
0.9364
1.0
0.9364
0.9671
5.8209
2.8727
18
0.5256
0.9409
1.0
0.9409
0.9696
Framework versions
Transformers 4.48.0.dev0
Pytorch 2.5.0+cu124
Datasets 3.1.0
Tokenizers 0.21.0
