metadata
library_name: transformers
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
model-index:
- name: rubert_level1
results: []
rubert_level1
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0971
- F1 Micro: 0.9515
- F1 Macro: 0.9504
- F1 Weighted: 0.9515
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: 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_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 0.1529 | 1.0 | 292 | 0.1426 | 0.9243 | 0.9222 | 0.9244 |
| 0.0557 | 2.0 | 584 | 0.1171 | 0.9354 | 0.9346 | 0.9363 |
| 0.0414 | 3.0 | 876 | 0.1106 | 0.9403 | 0.9393 | 0.9406 |
| 0.0288 | 4.0 | 1168 | 0.1015 | 0.9495 | 0.9485 | 0.9495 |
| 0.0154 | 5.0 | 1460 | 0.0971 | 0.9515 | 0.9504 | 0.9515 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2