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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lextreme |
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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: roberta-base-mapa_fine-ner |
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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: lextreme |
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type: lextreme |
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config: mapa_fine |
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split: test |
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args: mapa_fine |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7395134779750164 |
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- name: Recall |
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type: recall |
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value: 0.8236672524897481 |
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- name: F1 |
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type: f1 |
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value: 0.7793251576248873 |
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- name: Accuracy |
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type: accuracy |
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value: 0.991740752278482 |
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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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# roberta-base-mapa_fine-ner |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the lextreme dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0401 |
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- Precision: 0.7395 |
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- Recall: 0.8237 |
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- F1: 0.7793 |
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- Accuracy: 0.9917 |
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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: 16 |
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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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| 0.0877 | 1.0 | 1739 | 0.0495 | 0.6861 | 0.7595 | 0.7209 | 0.9903 | |
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| 0.0661 | 2.0 | 3478 | 0.0432 | 0.7278 | 0.8092 | 0.7663 | 0.9914 | |
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| 0.0633 | 3.0 | 5217 | 0.0403 | 0.7469 | 0.8128 | 0.7785 | 0.9919 | |
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| 0.059 | 4.0 | 6956 | 0.0401 | 0.7412 | 0.8196 | 0.7784 | 0.9918 | |
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| 0.063 | 5.0 | 8695 | 0.0400 | 0.7425 | 0.8200 | 0.7793 | 0.9918 | |
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| 0.0593 | 6.0 | 10434 | 0.0405 | 0.7332 | 0.8244 | 0.7761 | 0.9916 | |
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| 0.0595 | 7.0 | 12173 | 0.0400 | 0.7389 | 0.8222 | 0.7783 | 0.9917 | |
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| 0.0593 | 8.0 | 13912 | 0.0401 | 0.7390 | 0.8229 | 0.7787 | 0.9917 | |
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| 0.0594 | 9.0 | 15651 | 0.0402 | 0.7374 | 0.8240 | 0.7783 | 0.9917 | |
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| 0.0597 | 10.0 | 17390 | 0.0401 | 0.7395 | 0.8237 | 0.7793 | 0.9917 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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