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--- |
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base_model: dccuchile/distilbert-base-spanish-uncased |
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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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- f1 |
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model-index: |
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- name: distilbert-base-spanish-uncased-finetuned-text-intelligence |
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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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# distilbert-base-spanish-uncased-finetuned-text-intelligence |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6945 |
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- Accuracy: 0.8834 |
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- F1: 0.8827 |
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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: 1e-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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.0148 | 1.0 | 235 | 0.7880 | 0.7138 | 0.6551 | |
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| 0.6349 | 2.0 | 470 | 0.5415 | 0.8516 | 0.8500 | |
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| 0.4709 | 3.0 | 705 | 0.4505 | 0.8587 | 0.8613 | |
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| 0.3727 | 4.0 | 940 | 0.4156 | 0.8905 | 0.8900 | |
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| 0.3163 | 5.0 | 1175 | 0.4262 | 0.8905 | 0.8910 | |
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| 0.2695 | 6.0 | 1410 | 0.5090 | 0.8869 | 0.8874 | |
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| 0.2332 | 7.0 | 1645 | 0.5014 | 0.8869 | 0.8865 | |
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| 0.1811 | 8.0 | 1880 | 0.5735 | 0.8834 | 0.8827 | |
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| 0.1542 | 9.0 | 2115 | 0.5626 | 0.8940 | 0.8932 | |
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| 0.1192 | 10.0 | 2350 | 0.5680 | 0.8905 | 0.8900 | |
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| 0.124 | 11.0 | 2585 | 0.6291 | 0.8869 | 0.8857 | |
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| 0.0988 | 12.0 | 2820 | 0.6424 | 0.8834 | 0.8835 | |
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| 0.0933 | 13.0 | 3055 | 0.7085 | 0.8693 | 0.8668 | |
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| 0.0813 | 14.0 | 3290 | 0.6560 | 0.8905 | 0.8893 | |
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| 0.0599 | 15.0 | 3525 | 0.7175 | 0.8799 | 0.8793 | |
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| 0.0632 | 16.0 | 3760 | 0.6862 | 0.8799 | 0.8786 | |
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| 0.0489 | 17.0 | 3995 | 0.7064 | 0.8869 | 0.8858 | |
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| 0.0449 | 18.0 | 4230 | 0.7046 | 0.8834 | 0.8830 | |
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| 0.039 | 19.0 | 4465 | 0.6997 | 0.8799 | 0.8790 | |
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| 0.0388 | 20.0 | 4700 | 0.6945 | 0.8834 | 0.8827 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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