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--- |
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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: rubert-tiny2-1-4 |
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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-tiny2-1-4 |
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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: 0.3882 |
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- Accuracy: 0.9001 |
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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: 1e-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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- lr_scheduler_warmup_steps: 500 |
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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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| 1.9597 | 1.0 | 1500 | 1.1052 | 0.7613 | |
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| 0.9583 | 2.0 | 3000 | 0.8140 | 0.8157 | |
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| 0.7343 | 3.0 | 4500 | 0.6514 | 0.8502 | |
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| 0.6076 | 4.0 | 6000 | 0.5656 | 0.867 | |
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| 0.5257 | 5.0 | 7500 | 0.5115 | 0.8771 | |
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| 0.4694 | 6.0 | 9000 | 0.4748 | 0.8826 | |
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| 0.4296 | 7.0 | 10500 | 0.4477 | 0.8885 | |
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| 0.4006 | 8.0 | 12000 | 0.4295 | 0.8938 | |
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| 0.3753 | 9.0 | 13500 | 0.4159 | 0.896 | |
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| 0.358 | 10.0 | 15000 | 0.4066 | 0.8979 | |
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| 0.3417 | 11.0 | 16500 | 0.3994 | 0.8992 | |
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| 0.3296 | 12.0 | 18000 | 0.3943 | 0.8993 | |
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| 0.3203 | 13.0 | 19500 | 0.3914 | 0.8993 | |
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| 0.3158 | 14.0 | 21000 | 0.3889 | 0.9001 | |
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| 0.3126 | 15.0 | 22500 | 0.3882 | 0.9001 | |
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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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