--- widget: - text: Kuchli yomg‘irlar tufayli bir qator kuchli sel oqishi kuzatildi. example_title: Example 1 - text: >- Shu munosabat bilan O‘zbekiston Prezidenti global inqiroz sharoitida savdo-iqtisodiy hamkorlikni va hududlararo aloqalarni rivojlantirishning muhim masalalariga to‘xtalib o‘tdi. example_title: Example 2 tags: - generated_from_trainer datasets: - sinonimayzer/mixed-data language: - uz library_name: transformers pipeline_tag: fill-mask --- # UzRoBERTa-v2 This model achieves the following results on the evaluation set: - Loss: 1.9097 ## How to use ```python >>> from transformers import pipeline >>> unmasker = pipeline('fill-mask', model='sinonimayzer/UzRoBERTa-v2') >>> unmasker("Kuchli yomg‘irlar tufayli bir qator kuchli sel oqishi kuzatildi.") [{'score': 0.3318027853965759, 'token': 4877, 'token_str': ' hududlarda', 'sequence': 'Kuchli yomg‘irlar tufayli bir qator hududlarda kuchli sel oqishi kuzatildi.'}, {'score': 0.13175441324710846, 'token': 14470, 'token_str': ' viloyatlarda', 'sequence': 'Kuchli yomg‘irlar tufayli bir qator viloyatlarda kuchli sel oqishi kuzatildi.'}, {'score': 0.09735308587551117, 'token': 13555, 'token_str': ' tumanlarda', 'sequence': 'Kuchli yomg‘irlar tufayli bir qator tumanlarda kuchli sel oqishi kuzatildi.'}, {'score': 0.09112472087144852, 'token': 12261, 'token_str': ' shaharlarda', 'sequence': 'Kuchli yomg‘irlar tufayli bir qator shaharlarda kuchli sel oqishi kuzatildi.'}, {'score': 0.05940879508852959, 'token': 2767, 'token_str': ' joylarda', 'sequence': 'Kuchli yomg‘irlar tufayli bir qator joylarda kuchli sel oqishi kuzatildi.'}] ``` ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 92 - eval_batch_size: 92 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 500000 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:------:|:---------------:| | 2.3673 | 0.25 | 100000 | 2.4588 | | 2.0797 | 0.51 | 200000 | 2.1653 | | 1.9369 | 0.76 | 300000 | 2.0265 | | 1.8545 | 1.02 | 400000 | 1.9456 | | 1.8133 | 1.27 | 500000 | 1.9101 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0