| --- |
| library_name: transformers |
| base_model: ai-forever/ruBert-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: ruBert-large-topic_classification |
| 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-large-topic_classification |
| |
| This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7900 |
| - Precision: 0.8793 |
| - Recall: 0.8646 |
| - F1: 0.8688 |
| - Accuracy: 0.8824 |
| |
| ## 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-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 44 | 0.6327 | 0.8534 | 0.7883 | 0.8046 | 0.8186 | |
| | No log | 2.0 | 88 | 0.4897 | 0.8847 | 0.8401 | 0.8548 | 0.8676 | |
| | No log | 3.0 | 132 | 0.5957 | 0.8732 | 0.8617 | 0.8638 | 0.8676 | |
| | No log | 4.0 | 176 | 0.6598 | 0.8808 | 0.8658 | 0.8700 | 0.8824 | |
| | No log | 5.0 | 220 | 0.7086 | 0.8705 | 0.8589 | 0.8625 | 0.8775 | |
| | No log | 6.0 | 264 | 0.7445 | 0.8793 | 0.8646 | 0.8688 | 0.8824 | |
| | No log | 7.0 | 308 | 0.7661 | 0.8793 | 0.8646 | 0.8688 | 0.8824 | |
| | No log | 8.0 | 352 | 0.7795 | 0.8793 | 0.8646 | 0.8688 | 0.8824 | |
| | No log | 9.0 | 396 | 0.7870 | 0.8793 | 0.8646 | 0.8688 | 0.8824 | |
| | No log | 10.0 | 440 | 0.7900 | 0.8793 | 0.8646 | 0.8688 | 0.8824 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
