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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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- accuracy |
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model-index: |
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- name: ruBertTiny_attr_name_addv3 |
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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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# ruBertTiny_attr_name_addv3 |
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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: 0.2154 |
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- Accuracy: 0.9188 |
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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: cosine |
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- num_epochs: 5 |
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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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| 0.5515 | 0.2739 | 10000 | 0.4502 | 0.7949 | |
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| 0.49 | 0.5478 | 20000 | 0.3874 | 0.8205 | |
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| 0.4632 | 0.8217 | 30000 | 0.3556 | 0.8376 | |
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| 0.4367 | 1.0956 | 40000 | 0.3381 | 0.8419 | |
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| 0.4122 | 1.3695 | 50000 | 0.3138 | 0.8590 | |
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| 0.3989 | 1.6434 | 60000 | 0.2787 | 0.8932 | |
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| 0.389 | 1.9173 | 70000 | 0.2741 | 0.8846 | |
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| 0.3669 | 2.1912 | 80000 | 0.2523 | 0.9017 | |
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| 0.3566 | 2.4651 | 90000 | 0.2459 | 0.8932 | |
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| 0.3502 | 2.7391 | 100000 | 0.2343 | 0.9017 | |
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| 0.3458 | 3.0130 | 110000 | 0.2248 | 0.9145 | |
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| 0.3281 | 3.2869 | 120000 | 0.2203 | 0.9145 | |
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| 0.3255 | 3.5608 | 130000 | 0.2162 | 0.9145 | |
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| 0.3234 | 3.8347 | 140000 | 0.2176 | 0.9274 | |
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| 0.3174 | 4.1086 | 150000 | 0.2147 | 0.9188 | |
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| 0.3126 | 4.3825 | 160000 | 0.2138 | 0.9145 | |
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| 0.3127 | 4.6564 | 170000 | 0.2155 | 0.9188 | |
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| 0.3126 | 4.9303 | 180000 | 0.2154 | 0.9188 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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