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results – AI Model by AhmedMHalim | AlphaNeural AI
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AhmedMHalim
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safetensors
bert
generated_from_trainer
UBC-NLP/MARBERTv2
finetune
us
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results
This model is a fine-tuned version of
UBC-NLP/MARBERTv2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1921
Accuracy: 0.9316
Precision: 0.9246
Recall: 0.9370
F1: 0.9307
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: 64
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.2136
1.0
1161
0.1886
0.9320
0.9331
0.9279
0.9305
0.1554
2.0
2322
0.1921
0.9316
0.9246
0.9370
0.9307
Framework versions
Transformers 4.37.2
Pytorch 2.0.1+cu118
Datasets 2.16.1
Tokenizers 0.15.2
