Instructions to use 3liel/marbert-arabic-tweet-sentiment-stable with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3liel/marbert-arabic-tweet-sentiment-stable with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="3liel/marbert-arabic-tweet-sentiment-stable")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("3liel/marbert-arabic-tweet-sentiment-stable") model = AutoModelForSequenceClassification.from_pretrained("3liel/marbert-arabic-tweet-sentiment-stable", device_map="auto") - Notebooks
- Google Colab
- Kaggle
marbert-arabic-tweet-sentiment-stable
This model is a fine-tuned version of UBC-NLP/MARBERTv2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9006
- Accuracy: 0.7438
- F1: 0.7390
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 8
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0515 | 1.0 | 115 | 0.9030 | 0.5741 | 0.4974 |
| 0.8549 | 2.0 | 230 | 0.7719 | 0.6852 | 0.6537 |
| 0.7100 | 3.0 | 345 | 0.7589 | 0.6975 | 0.6779 |
| 0.5866 | 4.0 | 460 | 0.7610 | 0.7284 | 0.7213 |
| 0.4973 | 5.0 | 575 | 0.7742 | 0.7407 | 0.7365 |
| 0.4247 | 6.0 | 690 | 0.8592 | 0.7438 | 0.7387 |
| 0.3904 | 7.0 | 805 | 0.8710 | 0.7438 | 0.7405 |
| 0.3728 | 8.0 | 920 | 0.9006 | 0.7438 | 0.7390 |
Framework versions
- Transformers 5.15.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for 3liel/marbert-arabic-tweet-sentiment-stable
Base model
UBC-NLP/MARBERTv2