| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: emotion_classifier_roberta_optimized |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # emotion_classifier_roberta_optimized |
| |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1972 |
| - Macro F1: 0.4889 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 7 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Macro F1 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.2093 | 1.0 | 2614 | 0.2019 | 0.4586 | |
| | 0.1941 | 2.0 | 5228 | 0.1938 | 0.4815 | |
| | 0.1845 | 3.0 | 7842 | 0.1916 | 0.4921 | |
| | 0.1764 | 4.0 | 10456 | 0.1928 | 0.4918 | |
| | 0.1699 | 5.0 | 13070 | 0.1936 | 0.4963 | |
| | 0.1639 | 6.0 | 15684 | 0.1964 | 0.4872 | |
| | 0.1608 | 7.0 | 18298 | 0.1972 | 0.4889 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
|
|
