Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Laranya011/grievance-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laranya011/grievance-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Laranya011/grievance-intent-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Laranya011/grievance-intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("Laranya011/grievance-intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
grievance-intent-classifier
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5715
- Accuracy: 0.8235
- Macro F1: 0.8059
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 2.3255 | 1.0 | 77 | 1.8442 | 0.5752 | 0.5197 |
| 1.3356 | 2.0 | 154 | 0.9576 | 0.7908 | 0.7452 |
| 0.8913 | 3.0 | 231 | 0.6824 | 0.8105 | 0.7782 |
| 0.6168 | 4.0 | 308 | 0.5684 | 0.8497 | 0.8401 |
| 0.5292 | 5.0 | 385 | 0.5478 | 0.8693 | 0.8600 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 4.0.0
- Tokenizers 0.19.1
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Model tree for Laranya011/grievance-intent-classifier
Base model
FacebookAI/xlm-roberta-base