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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: cointegrated/rubert-tiny2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: rubert-tiny2-rus-MICRO
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+ results: []
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+ ---
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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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+ # rubert-tiny2-rus-MICRO
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+
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+ This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1743
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+ - F1: 0.8355
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+ - Roc Auc: 0.8967
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+ - Accuracy: 0.7732
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.2588 | 1.0 | 607 | 0.2564 | 0.6892 | 0.7777 | 0.6469 |
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+ | 0.1663 | 2.0 | 1214 | 0.1743 | 0.8322 | 0.8850 | 0.7668 |
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+ | 0.1014 | 3.0 | 1821 | 0.1481 | 0.8399 | 0.8829 | 0.7912 |
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+ | 0.0716 | 4.0 | 2428 | 0.1458 | 0.8433 | 0.8968 | 0.7861 |
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+ | 0.0496 | 5.0 | 3035 | 0.1440 | 0.8423 | 0.8945 | 0.7835 |
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+ | 0.0389 | 6.0 | 3642 | 0.1485 | 0.8458 | 0.9005 | 0.7887 |
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+ | 0.037 | 7.0 | 4249 | 0.1538 | 0.8428 | 0.8998 | 0.7822 |
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+ | 0.0218 | 8.0 | 4856 | 0.1623 | 0.8422 | 0.8997 | 0.7809 |
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+ | 0.0196 | 9.0 | 5463 | 0.1678 | 0.8420 | 0.9007 | 0.7796 |
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+ | 0.0204 | 10.0 | 6070 | 0.1743 | 0.8355 | 0.8967 | 0.7732 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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