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metadata
tags:
  - generated_from_trainer
datasets:
  - xnli
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: xnli
          type: xnli
          config: ar
          split: train
          args: ar
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.767065868263473
          - name: F1
            type: f1
            value: 0.767539058869847

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