| --- |
| library_name: transformers |
| base_model: eternalGenius/rubert_level2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: rubert_level2 |
| 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. --> |
|
|
| # rubert_level2 |
| |
| This model is a fine-tuned version of [eternalGenius/rubert_level2](https://huggingface.co/eternalGenius/rubert_level2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1661 |
| - F1 Micro: 0.7178 |
| - F1 Macro: 0.7076 |
| - F1 Weighted: 0.7118 |
| |
| ## 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: 5e-06 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - 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 |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 15 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.1082 | 1.0 | 97 | 0.1827 | 0.6862 | 0.6628 | 0.6653 | |
| | 0.0939 | 2.0 | 194 | 0.1743 | 0.7165 | 0.7000 | 0.7067 | |
| | 0.0861 | 3.0 | 291 | 0.1737 | 0.7198 | 0.7049 | 0.7055 | |
| | 0.0796 | 4.0 | 388 | 0.1735 | 0.7160 | 0.7074 | 0.7095 | |
| | 0.0771 | 5.0 | 485 | 0.1699 | 0.7089 | 0.6921 | 0.6923 | |
| | 0.0668 | 6.0 | 582 | 0.1661 | 0.7178 | 0.7076 | 0.7118 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
