Instructions to use arabizi/marbert-dialect-id3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arabizi/marbert-dialect-id3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arabizi/marbert-dialect-id3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arabizi/marbert-dialect-id3") model = AutoModelForSequenceClassification.from_pretrained("arabizi/marbert-dialect-id3") - Notebooks
- Google Colab
- Kaggle
marbert-dialect-id3
This model is a fine-tuned version of UBC-NLP/MARBERT on an unknown dataset.
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.1
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for arabizi/marbert-dialect-id3
Base model
UBC-NLP/MARBERT