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--- |
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license: cc-by-4.0 |
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base_model: dccuchile/tulio-chilean-spanish-bert |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: not-ner-v2_16batch |
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results: [] |
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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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# not-ner-v2_16batch |
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This model is a fine-tuned version of [dccuchile/tulio-chilean-spanish-bert](https://huggingface.co/dccuchile/tulio-chilean-spanish-bert) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1124 |
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- Accuracy: 0.9662 |
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- Precision: 0.9671 |
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- Recall: 0.9662 |
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- F1: 0.9665 |
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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: 5e-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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.0906 | 0.0798 | 250 | 0.1124 | 0.9662 | 0.9671 | 0.9662 | 0.9665 | |
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| 0.1008 | 0.1596 | 500 | 0.1416 | 0.9654 | 0.9652 | 0.9654 | 0.9653 | |
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| 0.0918 | 0.2394 | 750 | 0.1361 | 0.9662 | 0.9657 | 0.9662 | 0.9659 | |
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| 0.1077 | 0.3192 | 1000 | 0.1353 | 0.9636 | 0.9626 | 0.9636 | 0.9627 | |
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| 0.0863 | 0.3990 | 1250 | 0.1457 | 0.9590 | 0.9624 | 0.9590 | 0.9601 | |
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| 0.1048 | 0.4788 | 1500 | 0.1340 | 0.9653 | 0.9645 | 0.9653 | 0.9648 | |
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| 0.1066 | 0.5586 | 1750 | 0.1490 | 0.9631 | 0.9621 | 0.9631 | 0.9624 | |
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| 0.107 | 0.6384 | 2000 | 0.1479 | 0.9638 | 0.9641 | 0.9638 | 0.9639 | |
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| 0.1274 | 0.7182 | 2250 | 0.1331 | 0.9636 | 0.9634 | 0.9636 | 0.9635 | |
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| 0.1381 | 0.7980 | 2500 | 0.1577 | 0.9626 | 0.9616 | 0.9626 | 0.9618 | |
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| 0.1111 | 0.8778 | 2750 | 0.1353 | 0.9625 | 0.9637 | 0.9625 | 0.9630 | |
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| 0.132 | 0.9575 | 3000 | 0.1785 | 0.9592 | 0.9578 | 0.9592 | 0.9579 | |
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| 0.1464 | 1.0373 | 3250 | 0.1712 | 0.9610 | 0.9598 | 0.9610 | 0.9600 | |
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| 0.1279 | 1.1171 | 3500 | 0.1514 | 0.9630 | 0.9622 | 0.9630 | 0.9625 | |
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| 0.0947 | 1.1969 | 3750 | 0.1554 | 0.9625 | 0.9629 | 0.9625 | 0.9627 | |
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| 0.0958 | 1.2767 | 4000 | 0.1746 | 0.9617 | 0.9606 | 0.9617 | 0.9607 | |
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| 0.1212 | 1.3565 | 4250 | 0.1494 | 0.9628 | 0.9620 | 0.9628 | 0.9622 | |
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| 0.1097 | 1.4363 | 4500 | 0.1557 | 0.9635 | 0.9627 | 0.9635 | 0.9630 | |
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| 0.1288 | 1.5161 | 4750 | 0.1499 | 0.9642 | 0.9633 | 0.9642 | 0.9635 | |
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| 0.1043 | 1.5959 | 5000 | 0.1488 | 0.9614 | 0.9619 | 0.9614 | 0.9617 | |
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| 0.1016 | 1.6757 | 5250 | 0.1521 | 0.9616 | 0.9611 | 0.9616 | 0.9613 | |
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| 0.1073 | 1.7555 | 5500 | 0.1455 | 0.9618 | 0.9621 | 0.9618 | 0.9619 | |
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| 0.1264 | 1.8353 | 5750 | 0.2369 | 0.9143 | 0.9407 | 0.9143 | 0.9218 | |
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| 0.1211 | 1.9151 | 6000 | 0.1524 | 0.9613 | 0.9606 | 0.9613 | 0.9609 | |
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| 0.1071 | 1.9949 | 6250 | 0.1327 | 0.9574 | 0.9565 | 0.9574 | 0.9548 | |
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| 0.0915 | 2.0747 | 6500 | 0.1325 | 0.9640 | 0.9638 | 0.9640 | 0.9639 | |
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| 0.084 | 2.1545 | 6750 | 0.1321 | 0.9647 | 0.9646 | 0.9647 | 0.9646 | |
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| 0.0922 | 2.2343 | 7000 | 0.1486 | 0.9644 | 0.9635 | 0.9644 | 0.9637 | |
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| 0.0877 | 2.3141 | 7250 | 0.1281 | 0.9643 | 0.9648 | 0.9643 | 0.9645 | |
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| 0.0828 | 2.3939 | 7500 | 0.1425 | 0.9575 | 0.9591 | 0.9575 | 0.9582 | |
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| 0.0859 | 2.4737 | 7750 | 0.1283 | 0.9670 | 0.9665 | 0.9670 | 0.9667 | |
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| 0.0866 | 2.5535 | 8000 | 0.1189 | 0.9677 | 0.9671 | 0.9677 | 0.9673 | |
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| 0.0681 | 2.6333 | 8250 | 0.1195 | 0.9689 | 0.9682 | 0.9689 | 0.9683 | |
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| 0.0462 | 2.7131 | 8500 | 0.1408 | 0.9678 | 0.9670 | 0.9678 | 0.9670 | |
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| 0.0672 | 2.7929 | 8750 | 0.1233 | 0.9690 | 0.9684 | 0.9690 | 0.9686 | |
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| 0.0578 | 2.8726 | 9000 | 0.1232 | 0.9694 | 0.9689 | 0.9694 | 0.9691 | |
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| 0.0591 | 2.9524 | 9250 | 0.1219 | 0.9694 | 0.9689 | 0.9694 | 0.9690 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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