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bert-base-arabic-camelbert-msa-xnli-finetuned
vish88/bert-base-arabic-camelbert-msa-xnli-finetuned
bert-base-arabic-camelbert-msa-xnli-finetuned is a text classification model from vish88. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jan 27, 2023
- Updated
- Feb 15, 2023
- SHA
- ea74e3fa
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 27, 2023
- Updated
- Feb 15, 2023