| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: deepvk/RuModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: RuHalluBERT-base-v4 |
| 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. --> |
|
|
| # RuHalluBERT-base-v4 |
|
|
| This model is a fine-tuned version of [deepvk/RuModernBERT-base](https://huggingface.co/deepvk/RuModernBERT-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9101 |
| - F1 Macro: 0.7177 |
| - F1 Class1: 0.6720 |
| - F1 Class0: 0.7634 |
| - Accuracy: 0.7251 |
| - Precision Macro: 0.7252 |
| - Recall Macro: 0.7160 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 2e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 32 |
| - 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: cosine |
| - lr_scheduler_warmup_steps: 0.06 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Class1 | F1 Class0 | Accuracy | Precision Macro | Recall Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:--------:|:---------------:|:------------:| |
| | 11.2782 | 1.0 | 113 | 0.6490 | 0.6090 | 0.5076 | 0.7105 | 0.6353 | 0.6385 | 0.6155 | |
| | 10.4259 | 2.0 | 226 | 0.6731 | 0.5534 | 0.6783 | 0.4286 | 0.5884 | 0.7154 | 0.6228 | |
| | 8.9919 | 3.0 | 339 | 0.5547 | 0.7192 | 0.6884 | 0.75 | 0.7226 | 0.7197 | 0.7188 | |
| | 7.0874 | 4.0 | 452 | 0.5604 | 0.7349 | 0.6963 | 0.7734 | 0.7405 | 0.7396 | 0.7333 | |
| | 5.1057 | 5.0 | 565 | 0.6218 | 0.7091 | 0.7059 | 0.7124 | 0.7092 | 0.7144 | 0.7153 | |
| | 4.0620 | 6.0 | 678 | 0.6958 | 0.7181 | 0.7175 | 0.7188 | 0.7181 | 0.7250 | 0.7252 | |
| | 2.7632 | 7.0 | 791 | 0.7622 | 0.7370 | 0.6982 | 0.7758 | 0.7427 | 0.7421 | 0.7353 | |
| | 2.2915 | 8.0 | 904 | 0.8325 | 0.7164 | 0.6942 | 0.7386 | 0.7181 | 0.7160 | 0.7175 | |
| | 1.9114 | 9.0 | 1017 | 0.8926 | 0.7336 | 0.7079 | 0.7592 | 0.7360 | 0.7334 | 0.7338 | |
| | 1.2978 | 10.0 | 1130 | 0.9135 | 0.7269 | 0.7012 | 0.7526 | 0.7293 | 0.7266 | 0.7272 | |
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| ### Framework versions |
|
|
| - Transformers 5.8.1 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
|
|
