metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta_emotion_detection
results: []
roberta_emotion_detection
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1252
- Exact Match Accuracy: 0.2962
- F1 Micro: 0.4263
- F1 Macro: 0.4377
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: 3e-05
- train_batch_size: 96
- eval_batch_size: 192
- 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: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match Accuracy | F1 Micro | F1 Macro |
|---|---|---|---|---|---|---|
| 0.1926 | 1.0 | 393 | 0.1482 | 0.0339 | 0.0843 | 0.0336 |
| 0.136 | 2.0 | 786 | 0.1269 | 0.1808 | 0.3256 | 0.2574 |
| 0.1202 | 3.0 | 1179 | 0.1205 | 0.2185 | 0.3621 | 0.3371 |
| 0.1119 | 4.0 | 1572 | 0.1189 | 0.2601 | 0.4065 | 0.3926 |
| 0.1055 | 5.0 | 1965 | 0.1193 | 0.2801 | 0.4218 | 0.4206 |
| 0.1003 | 6.0 | 2358 | 0.1200 | 0.2811 | 0.4179 | 0.4180 |
| 0.0956 | 7.0 | 2751 | 0.1221 | 0.2829 | 0.4206 | 0.4269 |
| 0.0918 | 8.0 | 3144 | 0.1232 | 0.2929 | 0.4269 | 0.4353 |
| 0.0886 | 9.0 | 3537 | 0.1246 | 0.2974 | 0.4279 | 0.4397 |
| 0.086 | 10.0 | 3930 | 0.1252 | 0.2962 | 0.4263 | 0.4377 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1