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--- |
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base_model: dccuchile/bert-base-spanish-wwm-cased |
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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: bert-base-spanish-wwm-cased-ner |
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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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# bert-base-spanish-wwm-cased-ner |
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3695 |
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- Precision: 0.8640 |
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- Recall: 0.9126 |
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- F1: 0.8876 |
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- Accuracy: 0.9378 |
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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: 15 |
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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 | 280 | 0.3016 | 0.7779 | 0.8252 | 0.8009 | 0.9052 | |
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| 0.4113 | 2.0 | 560 | 0.2671 | 0.8150 | 0.8681 | 0.8407 | 0.9248 | |
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| 0.4113 | 3.0 | 840 | 0.2747 | 0.8181 | 0.8593 | 0.8382 | 0.9268 | |
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| 0.1179 | 4.0 | 1120 | 0.2875 | 0.8336 | 0.8978 | 0.8645 | 0.9312 | |
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| 0.1179 | 5.0 | 1400 | 0.3087 | 0.8529 | 0.9022 | 0.8769 | 0.9361 | |
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| 0.0608 | 6.0 | 1680 | 0.3449 | 0.8645 | 0.8978 | 0.8808 | 0.9351 | |
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| 0.0608 | 7.0 | 1960 | 0.3478 | 0.8539 | 0.8919 | 0.8725 | 0.9337 | |
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| 0.0306 | 8.0 | 2240 | 0.3495 | 0.8426 | 0.8963 | 0.8686 | 0.9337 | |
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| 0.0231 | 9.0 | 2520 | 0.3812 | 0.8660 | 0.9096 | 0.8873 | 0.9366 | |
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| 0.0231 | 10.0 | 2800 | 0.3346 | 0.8473 | 0.8963 | 0.8711 | 0.9386 | |
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| 0.0174 | 11.0 | 3080 | 0.3721 | 0.8583 | 0.9067 | 0.8818 | 0.9373 | |
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| 0.0174 | 12.0 | 3360 | 0.3778 | 0.8632 | 0.9067 | 0.8844 | 0.9371 | |
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| 0.014 | 13.0 | 3640 | 0.3733 | 0.8624 | 0.9096 | 0.8854 | 0.9366 | |
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| 0.014 | 14.0 | 3920 | 0.3709 | 0.8652 | 0.9126 | 0.8882 | 0.9398 | |
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| 0.013 | 15.0 | 4200 | 0.3695 | 0.8640 | 0.9126 | 0.8876 | 0.9378 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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