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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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- contratos_tceal |
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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: ner-bert-large-cased-pt-contratos_tceal |
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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: contratos_tceal |
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type: contratos_tceal |
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config: contratos_tceal |
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split: validation |
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args: contratos_tceal |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.918525703200776 |
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- name: Recall |
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type: recall |
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value: 0.9458964541368403 |
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- name: F1 |
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type: f1 |
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value: 0.9320101697695399 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9639352869753552 |
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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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# ner-bert-large-cased-pt-contratos_tceal |
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This model was trained from scratch on the contratos_tceal dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2229 |
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- Precision: 0.9185 |
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- Recall: 0.9459 |
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- F1: 0.9320 |
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- Accuracy: 0.9639 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 20 |
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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 | 363 | 0.1242 | 0.9164 | 0.9469 | 0.9314 | 0.9696 | |
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| 0.1307 | 2.0 | 726 | 0.1413 | 0.9197 | 0.9424 | 0.9309 | 0.9664 | |
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| 0.0831 | 3.0 | 1089 | 0.1366 | 0.9237 | 0.9477 | 0.9356 | 0.9682 | |
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| 0.0831 | 4.0 | 1452 | 0.1360 | 0.9283 | 0.9489 | 0.9385 | 0.9696 | |
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| 0.0646 | 5.0 | 1815 | 0.1572 | 0.9171 | 0.9427 | 0.9297 | 0.9646 | |
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| 0.0473 | 6.0 | 2178 | 0.1674 | 0.9069 | 0.9454 | 0.9257 | 0.9646 | |
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| 0.0367 | 7.0 | 2541 | 0.1783 | 0.9155 | 0.9414 | 0.9283 | 0.9644 | |
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| 0.0367 | 8.0 | 2904 | 0.1823 | 0.9244 | 0.9442 | 0.9342 | 0.9656 | |
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| 0.029 | 9.0 | 3267 | 0.1815 | 0.9190 | 0.9444 | 0.9315 | 0.9655 | |
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| 0.0227 | 10.0 | 3630 | 0.1945 | 0.9084 | 0.9457 | 0.9267 | 0.9617 | |
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| 0.0227 | 11.0 | 3993 | 0.1962 | 0.9134 | 0.9442 | 0.9285 | 0.9635 | |
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| 0.0188 | 12.0 | 4356 | 0.1893 | 0.9203 | 0.9442 | 0.9321 | 0.9651 | |
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| 0.0134 | 13.0 | 4719 | 0.1982 | 0.9181 | 0.9441 | 0.9309 | 0.9650 | |
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| 0.0126 | 14.0 | 5082 | 0.1962 | 0.9162 | 0.9447 | 0.9303 | 0.9667 | |
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| 0.0126 | 15.0 | 5445 | 0.2112 | 0.9196 | 0.9446 | 0.9319 | 0.9642 | |
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| 0.0099 | 16.0 | 5808 | 0.2138 | 0.9165 | 0.9449 | 0.9305 | 0.9630 | |
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| 0.007 | 17.0 | 6171 | 0.2110 | 0.9208 | 0.9447 | 0.9326 | 0.9652 | |
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| 0.0075 | 18.0 | 6534 | 0.2216 | 0.9210 | 0.9452 | 0.9330 | 0.9641 | |
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| 0.0075 | 19.0 | 6897 | 0.2232 | 0.9191 | 0.9461 | 0.9324 | 0.9640 | |
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| 0.0062 | 20.0 | 7260 | 0.2229 | 0.9185 | 0.9459 | 0.9320 | 0.9639 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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