Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Yousefmd/feedback-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yousefmd/feedback-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yousefmd/feedback-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yousefmd/feedback-classification") model = AutoModelForSequenceClassification.from_pretrained("Yousefmd/feedback-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| base_model: aubmindlab/bert-large-arabertv2 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: feedback-classification | |
| results: [] | |
| <!-- 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. --> | |
| # feedback-classification | |
| This model is a fine-tuned version of [aubmindlab/bert-large-arabertv2](https://huggingface.co/aubmindlab/bert-large-arabertv2) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3881 | |
| - Macro F1: 0.8586 | |
| - Accuracy: 0.8586 | |
| ## 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: 4 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 2 | |
| - total_train_batch_size: 8 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| | |
| | No log | 1.0 | 339 | 0.4434 | 0.8448 | 0.8468 | | |
| | 0.6508 | 2.0 | 678 | 0.3881 | 0.8586 | 0.8586 | | |
| ### Framework versions | |
| - Transformers 4.34.0 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.14.1 | |