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---
widget:
- text: Kuchli yomg‘irlar tufayli bir qator <mask> kuchli sel oqishi kuzatildi.
example_title: Example 1
- text: >-
Shu munosabat bilan O‘zbekiston Prezidenti global inqiroz sharoitida savdo-iqtisodiy hamkorlikni <mask> 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
---
<!-- 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. -->
# 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 <mask> 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 |