Instructions to use Vandita/TinyBERT-Linear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vandita/TinyBERT-Linear with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vandita/TinyBERT-Linear", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "Best_Validation": { | |
| "Accuracy": 0.9174608577263444, | |
| "Precision": 0.8740157480314961, | |
| "Recall": 0.9209606986899563, | |
| "F1": 0.8968743355305124, | |
| "MCC": 0.8289363201152266, | |
| "ROC_AUC": 0.9789405426732296 | |
| }, | |
| "SarcOjiTest1": { | |
| "Accuracy": 0.6088821250691754, | |
| "Precision": 0.6436578171091445, | |
| "Recall": 0.5740594580373586, | |
| "F1": 0.6068696982339035, | |
| "MCC": 0.22169400866840056, | |
| "ROC_AUC": 0.6539045251479979 | |
| }, | |
| "SarcOjiTest2": { | |
| "Accuracy": 0.6404272151898734, | |
| "Precision": 0.37516869095816463, | |
| "Recall": 0.6603325415676959, | |
| "F1": 0.4784853700516351, | |
| "MCC": 0.2565321672065399, | |
| "ROC_AUC": 0.7187829228280039 | |
| }, | |
| "Hyperparameters": { | |
| "Temperature": 3.0, | |
| "Alpha": 0.6 | |
| } | |
| } |