---
library_name: transformers
license: apache-2.0
base_model: deepvk/RuModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: RuHalluBERT-base-v5
  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-v5

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: 0.6279
- F1 Macro: 0.6522
- F1 Class1: 0.6352
- F1 Class0: 0.6693
- Accuracy: 0.6531
- Precision Macro: 0.6526
- Recall Macro: 0.6522

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:--------:|:---------------:|:------------:|
| 11.0041       | 1.0   | 123  | 0.6441          | 0.6245   | 0.5951    | 0.6539    | 0.6268   | 0.6269          | 0.6250       |
| 10.3103       | 2.0   | 246  | 0.6137          | 0.6680   | 0.6653    | 0.6708    | 0.6680   | 0.6683          | 0.6684       |
| 9.7315        | 3.0   | 369  | 0.6577          | 0.6269   | 0.7       | 0.5538    | 0.6412   | 0.6799          | 0.6479       |
| 8.9430        | 4.0   | 492  | 0.6604          | 0.6395   | 0.7205    | 0.5585    | 0.6577   | 0.7147          | 0.6653       |
| 7.8493        | 5.0   | 615  | 0.6796          | 0.6279   | 0.5474    | 0.7085    | 0.6454   | 0.6660          | 0.6393       |


### Framework versions

- Transformers 5.8.1
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2