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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lener_br |
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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-base-multilingual-cased-finetuned-ner-lenerBR |
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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: lener_br |
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type: lener_br |
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config: lener_br |
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split: validation |
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args: lener_br |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8457276795226933 |
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- name: Recall |
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type: recall |
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value: 0.8475336322869955 |
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- name: F1 |
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type: f1 |
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value: 0.8466296928327645 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9641886713579043 |
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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-base-multilingual-cased-finetuned-ner-lenerBR |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the lener_br dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1941 |
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- Precision: 0.8457 |
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- Recall: 0.8475 |
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- F1: 0.8466 |
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- Accuracy: 0.9642 |
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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: 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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- 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 | 245 | 0.2100 | 0.7326 | 0.7596 | 0.7459 | 0.9478 | |
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| No log | 2.0 | 490 | 0.1885 | 0.7737 | 0.8119 | 0.7923 | 0.9548 | |
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| 0.1595 | 3.0 | 735 | 0.1491 | 0.8056 | 0.8388 | 0.8218 | 0.9616 | |
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| 0.1595 | 4.0 | 980 | 0.1787 | 0.8369 | 0.8251 | 0.8310 | 0.9612 | |
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| 0.0311 | 5.0 | 1225 | 0.1788 | 0.8303 | 0.8601 | 0.8450 | 0.9646 | |
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| 0.0311 | 6.0 | 1470 | 0.2131 | 0.7985 | 0.8463 | 0.8217 | 0.9595 | |
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| 0.0156 | 7.0 | 1715 | 0.1879 | 0.8161 | 0.8635 | 0.8392 | 0.9630 | |
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| 0.0156 | 8.0 | 1960 | 0.1975 | 0.8445 | 0.8469 | 0.8457 | 0.9636 | |
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| 0.0091 | 9.0 | 2205 | 0.1979 | 0.8460 | 0.8422 | 0.8441 | 0.9635 | |
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| 0.0091 | 10.0 | 2450 | 0.1941 | 0.8457 | 0.8475 | 0.8466 | 0.9642 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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