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modernbert – AI Model by JahBless | AlphaNeural AI
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JahBless
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modernbert
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safetensors
deberta-v2
generated_from_trainer
microsoft/deberta-v3-base
finetune
mit
us
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modernbert
This model is a fine-tuned version of
microsoft/deberta-v3-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3914
Accuracy: 0.8959
Precision: 0.8962
Recall: 0.8959
F1: 0.8960
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.467
1.0
2000
0.4082
0.8595
0.8659
0.8595
0.8608
0.3228
2.0
4000
0.3473
0.8869
0.8873
0.8869
0.8866
0.2043
3.0
6000
0.3914
0.8959
0.8962
0.8959
0.8960
Framework versions
Transformers 4.40.1
Pytorch 2.3.0+cu121
Datasets 3.6.0
Tokenizers 0.19.1
