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--- |
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base_model: DeepPavlov/rubert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: rubert-base-cased-1-third |
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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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# rubert-base-cased-1-third |
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This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2935 |
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- Accuracy: 0.919 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 32 |
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- eval_batch_size: 32 |
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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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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.6641 | 1.0 | 1500 | 0.3723 | 0.9029 | |
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| 0.285 | 2.0 | 3000 | 0.3000 | 0.9154 | |
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| 0.1981 | 3.0 | 4500 | 0.2935 | 0.919 | |
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| 0.1488 | 4.0 | 6000 | 0.3073 | 0.9194 | |
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| 0.1139 | 5.0 | 7500 | 0.3401 | 0.9177 | |
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| 0.0902 | 6.0 | 9000 | 0.3662 | 0.9166 | |
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| 0.077 | 7.0 | 10500 | 0.3955 | 0.9175 | |
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| 0.0633 | 8.0 | 12000 | 0.4064 | 0.916 | |
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| 0.0548 | 9.0 | 13500 | 0.4286 | 0.9173 | |
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| 0.0487 | 10.0 | 15000 | 0.4429 | 0.916 | |
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| 0.0405 | 11.0 | 16500 | 0.4777 | 0.9195 | |
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| 0.0367 | 12.0 | 18000 | 0.4836 | 0.9202 | |
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| 0.0314 | 13.0 | 19500 | 0.4854 | 0.9194 | |
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| 0.0271 | 14.0 | 21000 | 0.5018 | 0.9175 | |
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| 0.023 | 15.0 | 22500 | 0.5123 | 0.9191 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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