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--- |
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license: apache-2.0 |
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base_model: bert-base-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-cased-finetuned-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: 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: 0.7640519805855644 |
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- name: Recall |
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type: recall |
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value: 0.818242790073776 |
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- name: F1 |
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type: f1 |
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value: 0.7902194154319487 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9615441099339138 |
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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-cased-finetuned-ner |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the lener_br dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Precision: 0.7641 |
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- Recall: 0.8182 |
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- F1: 0.7902 |
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- Accuracy: 0.9615 |
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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: 8 |
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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 | 432 | nan | 0.6807 | 0.7773 | 0.7258 | 0.9450 | |
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| 0.3019 | 2.0 | 864 | nan | 0.7244 | 0.7725 | 0.7476 | 0.9531 | |
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| 0.0871 | 3.0 | 1296 | nan | 0.7352 | 0.8192 | 0.7749 | 0.9571 | |
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| 0.0527 | 4.0 | 1728 | nan | 0.7455 | 0.7864 | 0.7654 | 0.9557 | |
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| 0.031 | 5.0 | 2160 | nan | 0.7334 | 0.7976 | 0.7642 | 0.9544 | |
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| 0.0223 | 6.0 | 2592 | nan | 0.7703 | 0.8343 | 0.8010 | 0.9624 | |
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| 0.0171 | 7.0 | 3024 | nan | 0.7279 | 0.8119 | 0.7676 | 0.9569 | |
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| 0.0171 | 8.0 | 3456 | nan | 0.7609 | 0.8067 | 0.7831 | 0.9613 | |
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| 0.012 | 9.0 | 3888 | nan | 0.7585 | 0.8152 | 0.7858 | 0.9608 | |
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| 0.0097 | 10.0 | 4320 | nan | 0.7641 | 0.8182 | 0.7902 | 0.9615 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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