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Thesis_modernBERT_final – AI Model by Col474 | AlphaNeural AI
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Col474
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Thesis_modernBERT_final
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transformers
tensorboard
safetensors
modernbert
text-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
endpoints_compatible
us
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Thesis_modernBERT_final
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6932
F1: 0.7881
Accuracy: 0.7914
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: 3.912047350705144e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
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: linear
lr_scheduler_warmup_steps: 0.09180460212108857
num_epochs: 5
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Accuracy
3.8628
1.0
84
0.7282
0.7368
0.7446
2.5333
2.0
168
0.6384
0.8037
0.8058
1.8198
3.0
252
0.6710
0.7801
0.7842
1.4099
4.0
336
0.6932
0.7881
0.7914
Framework versions
Transformers 5.5.4
Pytorch 2.10.0+cu128
Datasets 4.8.4
Tokenizers 0.22.2
