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--- |
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license: apache-2.0 |
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tags: |
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- text-classification |
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- generated_from_trainer |
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datasets: |
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- xnli |
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metrics: |
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- accuracy |
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base_model: bert-base-multilingual-cased |
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model-index: |
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- name: xnli_m_bert_only_ru |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: xnli |
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type: xnli |
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config: ru |
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split: train |
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args: ru |
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metrics: |
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- type: accuracy |
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value: 0.7192771084337349 |
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name: Accuracy |
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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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# xnli_m_bert_only_ru |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the xnli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4375 |
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- Accuracy: 0.7193 |
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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: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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: 10 |
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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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| 0.6663 | 1.0 | 3068 | 0.7367 | 0.6908 | |
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| 0.5792 | 2.0 | 6136 | 0.6650 | 0.7229 | |
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| 0.4875 | 3.0 | 9204 | 0.6935 | 0.7285 | |
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| 0.3989 | 4.0 | 12272 | 0.7481 | 0.7233 | |
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| 0.3177 | 5.0 | 15340 | 0.7786 | 0.7277 | |
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| 0.2429 | 6.0 | 18408 | 0.9419 | 0.7209 | |
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| 0.1871 | 7.0 | 21476 | 1.0537 | 0.7237 | |
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| 0.1388 | 8.0 | 24544 | 1.1777 | 0.7225 | |
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| 0.106 | 9.0 | 27612 | 1.3488 | 0.7209 | |
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| 0.0776 | 10.0 | 30680 | 1.4375 | 0.7193 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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