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ABL_trad_l

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
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  2. runs/Jun05_20-53-05_PcJavierOmen/events.out.tfevents.1717613586.PcJavierOmen.25944.0 +2 -2
  3. runs/Jun05_20-53-05_PcJavierOmen/events.out.tfevents.1717620564.PcJavierOmen.25944.1 +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_l
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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_l
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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: 3.2495
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+ - Accuracy: 0.6833
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+ - F1: 0.6809
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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: 6
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+ - eval_batch_size: 6
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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: 42
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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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+ | 0.9228 | 1.0 | 2000 | 0.9053 | 0.5817 | 0.5807 |
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+ | 0.8293 | 2.0 | 4000 | 0.8649 | 0.6 | 0.5927 |
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+ | 0.7665 | 3.0 | 6000 | 0.8310 | 0.6217 | 0.6206 |
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+ | 0.7292 | 4.0 | 8000 | 0.8270 | 0.6358 | 0.6316 |
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+ | 0.6773 | 5.0 | 10000 | 0.8149 | 0.6558 | 0.6520 |
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+ | 0.648 | 6.0 | 12000 | 0.8207 | 0.6492 | 0.6471 |
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+ | 0.5912 | 7.0 | 14000 | 0.8353 | 0.6508 | 0.6487 |
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+ | 0.5558 | 8.0 | 16000 | 0.8601 | 0.66 | 0.6585 |
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+ | 0.5169 | 9.0 | 18000 | 0.9048 | 0.6617 | 0.6585 |
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+ | 0.4678 | 10.0 | 20000 | 0.9497 | 0.6675 | 0.6646 |
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+ | 0.4281 | 11.0 | 22000 | 1.0488 | 0.6633 | 0.6575 |
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+ | 0.413 | 12.0 | 24000 | 1.1182 | 0.66 | 0.6557 |
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+ | 0.389 | 13.0 | 26000 | 1.2184 | 0.6758 | 0.6718 |
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+ | 0.3501 | 14.0 | 28000 | 1.3527 | 0.665 | 0.6613 |
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+ | 0.3572 | 15.0 | 30000 | 1.4490 | 0.6692 | 0.6642 |
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+ | 0.3136 | 16.0 | 32000 | 1.5910 | 0.6733 | 0.6713 |
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+ | 0.3247 | 17.0 | 34000 | 1.7505 | 0.6708 | 0.6683 |
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+ | 0.2824 | 18.0 | 36000 | 1.9347 | 0.6617 | 0.6551 |
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+ | 0.2579 | 19.0 | 38000 | 2.0703 | 0.6733 | 0.6692 |
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+ | 0.2641 | 20.0 | 40000 | 2.1537 | 0.6658 | 0.6609 |
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+ | 0.1788 | 21.0 | 42000 | 2.2683 | 0.6758 | 0.6728 |
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+ | 0.2099 | 22.0 | 44000 | 2.3347 | 0.6692 | 0.6670 |
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+ | 0.1637 | 23.0 | 46000 | 2.4836 | 0.675 | 0.6712 |
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+ | 0.1671 | 24.0 | 48000 | 2.5688 | 0.6775 | 0.6731 |
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+ | 0.1455 | 25.0 | 50000 | 2.6975 | 0.6767 | 0.6699 |
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+ | 0.1425 | 26.0 | 52000 | 2.7016 | 0.6742 | 0.6716 |
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+ | 0.1406 | 27.0 | 54000 | 2.7527 | 0.6825 | 0.6785 |
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+ | 0.1234 | 28.0 | 56000 | 2.8701 | 0.6758 | 0.6710 |
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+ | 0.0967 | 29.0 | 58000 | 2.8947 | 0.685 | 0.6803 |
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+ | 0.0864 | 30.0 | 60000 | 2.9296 | 0.6742 | 0.6723 |
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+ | 0.0956 | 31.0 | 62000 | 2.9966 | 0.6808 | 0.6762 |
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+ | 0.0835 | 32.0 | 64000 | 3.0406 | 0.6808 | 0.6759 |
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+ | 0.073 | 33.0 | 66000 | 3.0750 | 0.6725 | 0.6680 |
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+ | 0.0618 | 34.0 | 68000 | 3.0261 | 0.6808 | 0.6769 |
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+ | 0.0833 | 35.0 | 70000 | 3.0812 | 0.685 | 0.6817 |
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+ | 0.0478 | 36.0 | 72000 | 3.1352 | 0.6825 | 0.6784 |
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+ | 0.0712 | 37.0 | 74000 | 3.1516 | 0.68 | 0.6780 |
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+ | 0.0712 | 38.0 | 76000 | 3.2088 | 0.6708 | 0.6664 |
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+ | 0.0407 | 39.0 | 78000 | 3.2520 | 0.6858 | 0.6828 |
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+ | 0.0659 | 40.0 | 80000 | 3.2791 | 0.6792 | 0.6751 |
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+ | 0.0468 | 41.0 | 82000 | 3.2433 | 0.6875 | 0.6826 |
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+ | 0.0571 | 42.0 | 84000 | 3.2495 | 0.6833 | 0.6809 |
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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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