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mrovejaxd
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ABL_trad_k

Text Classification
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bert
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  2. runs/May27_21-43-06_PcJavierOmen/events.out.tfevents.1716838986.PcJavierOmen.17520.0 +2 -2
  3. runs/May27_21-43-06_PcJavierOmen/events.out.tfevents.1716844303.PcJavierOmen.17520.1 +3 -0
README.md ADDED
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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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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: ABL_trad_k
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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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+ # ABL_trad_k
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+
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.8641
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+ - Accuracy: 0.6842
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+ - F1: 0.6826
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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: 1e-06
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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: 36
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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+ | 0.9411 | 1.0 | 1500 | 0.9017 | 0.5792 | 0.5764 |
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+ | 0.8328 | 2.0 | 3000 | 0.8458 | 0.62 | 0.6188 |
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+ | 0.8006 | 3.0 | 4500 | 0.8183 | 0.64 | 0.6391 |
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+ | 0.7283 | 4.0 | 6000 | 0.8154 | 0.6442 | 0.6430 |
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+ | 0.7006 | 5.0 | 7500 | 0.7978 | 0.6492 | 0.6487 |
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+ | 0.6555 | 6.0 | 9000 | 0.8009 | 0.6542 | 0.6536 |
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+ | 0.6263 | 7.0 | 10500 | 0.8033 | 0.6617 | 0.6612 |
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+ | 0.5805 | 8.0 | 12000 | 0.8155 | 0.6658 | 0.6657 |
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+ | 0.5385 | 9.0 | 13500 | 0.8608 | 0.675 | 0.6729 |
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+ | 0.5108 | 10.0 | 15000 | 0.8545 | 0.6733 | 0.6732 |
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+ | 0.4791 | 11.0 | 16500 | 0.8950 | 0.6758 | 0.6750 |
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+ | 0.4423 | 12.0 | 18000 | 0.9145 | 0.6792 | 0.6790 |
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+ | 0.4295 | 13.0 | 19500 | 0.9497 | 0.6708 | 0.6707 |
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+ | 0.3782 | 14.0 | 21000 | 1.0309 | 0.6742 | 0.6734 |
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+ | 0.3656 | 15.0 | 22500 | 1.0706 | 0.6783 | 0.6774 |
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+ | 0.3312 | 16.0 | 24000 | 1.1327 | 0.6733 | 0.6730 |
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+ | 0.3008 | 17.0 | 25500 | 1.1870 | 0.6825 | 0.6822 |
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+ | 0.2851 | 18.0 | 27000 | 1.3284 | 0.685 | 0.6847 |
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+ | 0.2636 | 19.0 | 28500 | 1.4260 | 0.6858 | 0.6851 |
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+ | 0.2752 | 20.0 | 30000 | 1.4733 | 0.6833 | 0.6833 |
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+ | 0.2231 | 21.0 | 31500 | 1.6163 | 0.68 | 0.6800 |
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+ | 0.2052 | 22.0 | 33000 | 1.7674 | 0.6792 | 0.6786 |
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+ | 0.198 | 23.0 | 34500 | 1.8474 | 0.6833 | 0.6827 |
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+ | 0.1854 | 24.0 | 36000 | 1.9509 | 0.6775 | 0.6766 |
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+ | 0.1944 | 25.0 | 37500 | 2.0660 | 0.68 | 0.6790 |
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+ | 0.1649 | 26.0 | 39000 | 2.1718 | 0.6825 | 0.6812 |
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+ | 0.1443 | 27.0 | 40500 | 2.3664 | 0.68 | 0.6791 |
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+ | 0.1251 | 28.0 | 42000 | 2.4144 | 0.6833 | 0.6827 |
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+ | 0.1357 | 29.0 | 43500 | 2.4407 | 0.6875 | 0.6875 |
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+ | 0.1279 | 30.0 | 45000 | 2.4419 | 0.6933 | 0.6932 |
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+ | 0.1112 | 31.0 | 46500 | 2.5989 | 0.6833 | 0.6828 |
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+ | 0.098 | 32.0 | 48000 | 2.6390 | 0.68 | 0.6792 |
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+ | 0.0864 | 33.0 | 49500 | 2.7293 | 0.6792 | 0.6780 |
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+ | 0.0897 | 34.0 | 51000 | 2.7814 | 0.6833 | 0.6820 |
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+ | 0.0869 | 35.0 | 52500 | 2.8468 | 0.68 | 0.6787 |
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+ | 0.0834 | 36.0 | 54000 | 2.8641 | 0.6842 | 0.6826 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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