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bert-base-arabic-camelbert-msa-xnli-finetuned – AI Model by vish88 | AlphaNeural AI
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vish88
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bert-base-arabic-camelbert-msa-xnli-finetuned
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
xnli
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-arabic-camelbert-msa-xnli-finetuned
This model is a fine-tuned version of
CAMeL-Lab/bert-base-arabic-camelbert-msa
on the xnli dataset. It achieves the following results on the evaluation set:
eval_loss: 0.6284
eval_accuracy: 0.7433
eval_f1: 0.7429
eval_runtime: 77.5483
eval_samples_per_second: 64.605
eval_steps_per_second: 64.605
epoch: 1.0
step: 24543
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: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
