---
datasets:
- SetFit/emotion
language:
- en
base_model:
- microsoft/deberta-v3-base
library_name: transformers
---
# Training
- Code: [Training Notebook](https://www.kaggle.com/code/shihhsuanchen/emotion-detection-train)
- Criteria: Best validation loss
- Training configuration:

  ```json
  {
    "seed": 567,
    "ddp": true,
    "learning_rate": 5e-05,
    "train_batch_size": 80,
    "valid_batch_size": 80,
    "lr_scheduler_type": "linear",
    "num_epochs": 20,
    "num_warmup_steps": 125,
    "max_train_steps": null,
    "max_valid_steps": null,
    "max_length": 72
  }
  ```
  
# Evaluation
- Code: [Evaluation Notebook](https://www.kaggle.com/code/shihhsuanchen/emotion-detection-eval)
- Results
| 	        |  sadness |   joy    |   love   |   anger  |   fear   | surprise | Total (Macro) |
|-----------|----------|----------|----------|----------|----------|----------|---------------|
| Accuracy  | 0.985420 | 0.965309 | 0.974359 | 0.983912 | 0.980392 | 0.985923 | 0.979219      |
| Precision | 0.966102 | 0.936709 | 0.858108 | 0.980159 | 0.868526 | 1.000000 | 0.934934      |
| Recall    | 0.984456 | 0.965217 | 0.808917 | 0.901460 | 0.973214 | 0.569231 | 0.867083      |
| F1-Score  | 0.975192 | 0.950749 | 0.832787 | 0.939163 | 0.917895 | 0.725490 | 0.890213      |