Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42") model = AutoModelForSequenceClassification.from_pretrained("notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42
This model is a fine-tuned version of jcblaise/roberta-tagalog-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5196
- Accuracy: 0.9733
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: 5.0456033682942977e-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: cosine
- lr_scheduler_warmup_steps: 150
- num_epochs: 8
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1306 | 1.0 | 150 | 0.6238 | 0.94 |
| 0.5249 | 2.0 | 300 | 0.5522 | 0.9633 |
| 0.475 | 3.0 | 450 | 0.5665 | 0.9567 |
| 0.4529 | 4.0 | 600 | 0.5435 | 0.97 |
| 0.4526 | 5.0 | 750 | 0.5166 | 0.9733 |
| 0.448 | 6.0 | 900 | 0.5175 | 0.9767 |
| 0.4479 | 7.0 | 1050 | 0.5203 | 0.9733 |
| 0.4478 | 8.0 | 1200 | 0.5196 | 0.9733 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for notlath/RoBERTa-Tagalog-base-Symptom2Disease_WITH-DROPOUT-42
Base model
jcblaise/roberta-tagalog-base