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custom-ner-model-viajes

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+ ---
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+ tags:
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+ - generated_from_trainer
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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: custom-ner-model2
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+ results: []
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+ ---
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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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+
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+ # custom-ner-model2
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+
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+ This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2050
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+ - Precision: 0.8542
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+ - Recall: 0.8817
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+ - F1: 0.8677
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+ - Accuracy: 0.9595
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 20
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+
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+ ### Training results
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+
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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 | 105 | 0.5185 | 0.5840 | 0.5484 | 0.5656 | 0.8596 |
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+ | No log | 2.0 | 210 | 0.3212 | 0.7365 | 0.7312 | 0.7338 | 0.9050 |
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+ | No log | 3.0 | 315 | 0.2440 | 0.8123 | 0.8065 | 0.8094 | 0.9389 |
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+ | No log | 4.0 | 420 | 0.2186 | 0.8014 | 0.8100 | 0.8057 | 0.9431 |
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+ | 0.4107 | 5.0 | 525 | 0.1911 | 0.8481 | 0.8602 | 0.8541 | 0.9516 |
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+ | 0.4107 | 6.0 | 630 | 0.1931 | 0.8235 | 0.8530 | 0.8380 | 0.9546 |
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+ | 0.4107 | 7.0 | 735 | 0.1720 | 0.8368 | 0.8638 | 0.8501 | 0.9570 |
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+ | 0.4107 | 8.0 | 840 | 0.1858 | 0.8385 | 0.8746 | 0.8561 | 0.9583 |
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+ | 0.4107 | 9.0 | 945 | 0.1858 | 0.85 | 0.8530 | 0.8515 | 0.9552 |
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+ | 0.0667 | 10.0 | 1050 | 0.1961 | 0.8526 | 0.8710 | 0.8617 | 0.9564 |
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+ | 0.0667 | 11.0 | 1155 | 0.1970 | 0.8537 | 0.8781 | 0.8657 | 0.9589 |
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+ | 0.0667 | 12.0 | 1260 | 0.1865 | 0.8478 | 0.8781 | 0.8627 | 0.9619 |
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+ | 0.0667 | 13.0 | 1365 | 0.1994 | 0.8379 | 0.8710 | 0.8541 | 0.9583 |
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+ | 0.0667 | 14.0 | 1470 | 0.1913 | 0.8507 | 0.8781 | 0.8642 | 0.9613 |
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+ | 0.0274 | 15.0 | 1575 | 0.2064 | 0.8512 | 0.8817 | 0.8662 | 0.9595 |
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+ | 0.0274 | 16.0 | 1680 | 0.2053 | 0.8478 | 0.8781 | 0.8627 | 0.9601 |
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+ | 0.0274 | 17.0 | 1785 | 0.2037 | 0.8576 | 0.8853 | 0.8713 | 0.9601 |
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+ | 0.0274 | 18.0 | 1890 | 0.2056 | 0.8632 | 0.8817 | 0.8723 | 0.9595 |
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+ | 0.0274 | 19.0 | 1995 | 0.2066 | 0.8571 | 0.8817 | 0.8693 | 0.9601 |
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+ | 0.0162 | 20.0 | 2100 | 0.2050 | 0.8542 | 0.8817 | 0.8677 | 0.9595 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2