metadata
library_name: transformers
license: mit
base_model: elmurod1202/bertbek-news-big-cased
tags:
- generated_from_trainer
model-index:
- name: bertbek-news-classifier
results: []
datasets:
- elmurod1202/daryo_news_categorized
language:
- uz
metrics:
- accuracy
pipeline_tag: text-classification
bertbek-news-classifier
This model is a fine-tuned version of elmurod1202/bertbek-news-big-cased on the daryo news dataset elmurod1202/daryo_news_categorized. It achieves the following results on the evaluation set:
- Loss: 0.2955
Model description
BERTbek model fine-tuned for text classification
Intended uses & limitations
Text classification model for Uzbek texts
Training and evaluation data
Daryo news dataset: elmurod1202/daryo_news_categorized
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.22 | 1.0 | 3378 | 0.1993 |
| 0.1194 | 2.0 | 6756 | 0.2308 |
| 0.0633 | 3.0 | 10134 | 0.2955 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1