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sinonimayzer
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UzRoBERTa-v2

Fill-Mask
Transformers
Safetensors
Uzbek
roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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README.md CHANGED
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  ---
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- widget:
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- - text: Kuchli yomg‘irlar tufayli bir qator <mask> kuchli sel oqishi kuzatildi.
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- example_title: Example 1
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- - text: >-
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- Shu munosabat bilan O‘zbekiston Prezidenti global inqiroz sharoitida savdo-iqtisodiy hamkorlikni <mask> va hududlararo aloqalarni rivojlantirishning muhim masalalariga to‘xtalib o‘tdi.
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- example_title: Example 2
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- datasets:
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- - sinonimayzer/mixed-data
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- language:
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- - uz
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- pipeline_tag: fill-mask
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  ---
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  ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: UzRoBERTa-v2
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+ results: []
 
 
 
 
 
 
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # UzRoBERTa-v2
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9097
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 92
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+ - eval_batch_size: 92
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - training_steps: 500000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:------:|:---------------:|
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+ | 6.3907 | 0.03 | 10000 | 6.3152 |
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+ | 5.9936 | 0.05 | 20000 | 5.7963 |
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+ | 3.6265 | 0.08 | 30000 | 3.5652 |
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+ | 3.0828 | 0.1 | 40000 | 3.1101 |
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+ | 2.8485 | 0.13 | 50000 | 2.8866 |
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+ | 2.6924 | 0.15 | 60000 | 2.7570 |
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+ | 2.5799 | 0.18 | 70000 | 2.6464 |
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+ | 2.4943 | 0.2 | 80000 | 2.5785 |
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+ | 2.4246 | 0.23 | 90000 | 2.5101 |
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+ | 2.3673 | 0.25 | 100000 | 2.4588 |
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+ | 2.3233 | 0.28 | 110000 | 2.4183 |
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+ | 2.28 | 0.3 | 120000 | 2.3632 |
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+ | 2.2451 | 0.33 | 130000 | 2.3335 |
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+ | 2.2113 | 0.36 | 140000 | 2.3124 |
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+ | 2.1853 | 0.38 | 150000 | 2.2717 |
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+ | 2.1566 | 0.41 | 160000 | 2.2435 |
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+ | 2.1344 | 0.43 | 170000 | 2.2302 |
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+ | 2.1157 | 0.46 | 180000 | 2.2068 |
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+ | 2.0926 | 0.48 | 190000 | 2.1794 |
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+ | 2.0797 | 0.51 | 200000 | 2.1653 |
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+ | 2.056 | 0.53 | 210000 | 2.1497 |
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+ | 2.043 | 0.56 | 220000 | 2.1302 |
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+ | 2.0217 | 0.58 | 230000 | 2.1162 |
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+ | 2.0112 | 0.61 | 240000 | 2.1003 |
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+ | 1.9934 | 0.64 | 250000 | 2.0877 |
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+ | 1.9855 | 0.66 | 260000 | 2.0697 |
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+ | 1.9756 | 0.69 | 270000 | 2.0601 |
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+ | 1.9596 | 0.71 | 280000 | 2.0457 |
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+ | 1.9477 | 0.74 | 290000 | 2.0407 |
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+ | 1.9369 | 0.76 | 300000 | 2.0265 |
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+ | 1.9342 | 0.79 | 310000 | 2.0106 |
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+ | 1.9183 | 0.81 | 320000 | 2.0076 |
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+ | 1.9076 | 0.84 | 330000 | 1.9999 |
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+ | 1.8994 | 0.86 | 340000 | 1.9924 |
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+ | 1.8968 | 0.89 | 350000 | 1.9871 |
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+ | 1.8897 | 0.91 | 360000 | 1.9787 |
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+ | 1.8769 | 0.94 | 370000 | 1.9678 |
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+ | 1.8727 | 0.97 | 380000 | 1.9659 |
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+ | 1.8675 | 0.99 | 390000 | 1.9546 |
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+ | 1.8545 | 1.02 | 400000 | 1.9456 |
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+ | 1.8515 | 1.04 | 410000 | 1.9425 |
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+ | 1.8397 | 1.07 | 420000 | 1.9416 |
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+ | 1.8406 | 1.09 | 430000 | 1.9343 |
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+ | 1.8332 | 1.12 | 440000 | 1.9273 |
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+ | 1.8325 | 1.14 | 450000 | 1.9257 |
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+ | 1.8258 | 1.17 | 460000 | 1.9219 |
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+ | 1.8239 | 1.19 | 470000 | 1.9168 |
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+ | 1.8173 | 1.22 | 480000 | 1.9163 |
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+ | 1.8155 | 1.25 | 490000 | 1.9113 |
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+ | 1.8133 | 1.27 | 500000 | 1.9101 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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