metadata
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: []
RuHalluBERT-base-v4
This model is a fine-tuned version of 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
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 |
Framework versions
- Transformers 5.8.1
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2