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bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned – AI Model by SarahAdnan | AlphaNeural AI
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SarahAdnan
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bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
xnli
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
This model is a fine-tuned version of
aubmindlab/bert-base-arabertv02
on the xnli dataset. It achieves the following results on the evaluation set:
Loss: 0.5796
Accuracy: 0.7671
F1: 0.7675
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5804
1.0
12271
0.5796
0.7671
0.7675
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2
