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--- |
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library_name: transformers |
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base_model: ai-forever/ruBert-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- universal_dependencies |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: ruBert-large-upos |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: universal_dependencies |
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type: universal_dependencies |
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config: ru_syntagrus |
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split: validation |
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args: ru_syntagrus |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8307441967265208 |
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- name: Recall |
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type: recall |
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value: 0.7502322735093846 |
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- name: F1 |
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type: f1 |
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value: 0.783084706036028 |
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- name: Accuracy |
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type: accuracy |
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value: 0.868562326706389 |
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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-large-upos |
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This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on the universal_dependencies dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4344 |
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- Precision: 0.8307 |
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- Recall: 0.7502 |
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- F1: 0.7831 |
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- Accuracy: 0.8686 |
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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: 16 |
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- eval_batch_size: 8 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 338 | 0.4759 | 0.7967 | 0.7249 | 0.7532 | 0.8557 | |
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| No log | 2.0 | 676 | 0.4344 | 0.8307 | 0.7502 | 0.7831 | 0.8686 | |
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| No log | 3.0 | 1014 | 0.6906 | 0.7842 | 0.7480 | 0.7563 | 0.8674 | |
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| No log | 4.0 | 1352 | 0.4757 | 0.8185 | 0.7578 | 0.7777 | 0.8816 | |
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| No log | 5.0 | 1690 | 0.6291 | 0.7791 | 0.7721 | 0.7670 | 0.8792 | |
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| No log | 6.0 | 2028 | 0.6466 | 0.7967 | 0.7677 | 0.7721 | 0.8863 | |
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| No log | 7.0 | 2366 | 0.7072 | 0.7751 | 0.7700 | 0.7704 | 0.8809 | |
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| No log | 8.0 | 2704 | 0.7623 | 0.7957 | 0.7678 | 0.7749 | 0.8838 | |
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| No log | 9.0 | 3042 | 0.7458 | 0.7922 | 0.7716 | 0.7773 | 0.8873 | |
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| No log | 10.0 | 3380 | 0.7560 | 0.7916 | 0.7709 | 0.7767 | 0.8869 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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