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ModernBERT-base-finetuned-demo – AI Model by dassum | AlphaNeural AI
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ModernBERT-base-finetuned-demo
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transformers
safetensors
bert
multiple-choice
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
endpoints_compatible
us
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ModernBERT-base-finetuned-demo
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: 1.0986
Accuracy: 0.3468
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
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: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.1016
0.9994
1454
1.0986
0.3396
1.0999
1.9994
2908
1.0986
0.3661
1.0993
2.9994
4362
1.0986
0.3468
Framework versions
Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
