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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- null |
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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: bert-srb-ner-setimes |
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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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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.9589059598176599 |
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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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# bert-srb-ner-setimes |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1430 |
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- Precision: 0.7811 |
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- Recall: 0.8141 |
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- F1: 0.7973 |
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- Accuracy: 0.9589 |
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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: 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: 5 |
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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 | 207 | 0.2001 | 0.7109 | 0.7505 | 0.7301 | 0.9422 | |
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| No log | 2.0 | 414 | 0.1581 | 0.7347 | 0.7792 | 0.7563 | 0.9510 | |
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| 0.2354 | 3.0 | 621 | 0.1506 | 0.7612 | 0.8034 | 0.7818 | 0.9555 | |
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| 0.2354 | 4.0 | 828 | 0.1534 | 0.7728 | 0.8082 | 0.7901 | 0.9569 | |
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| 0.0883 | 5.0 | 1035 | 0.1430 | 0.7811 | 0.8141 | 0.7973 | 0.9589 | |
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### Framework versions |
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- Transformers 4.9.2 |
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- Pytorch 1.9.0 |
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- Datasets 1.11.0 |
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- Tokenizers 0.10.1 |
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