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FNST_trad_j

Text Classification
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bert
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  1. README.md +92 -0
  2. runs/May26_04-03-33_PcJavierOmen/events.out.tfevents.1716689014.PcJavierOmen.27568.2 +2 -2
  3. runs/May26_04-03-33_PcJavierOmen/events.out.tfevents.1716696645.PcJavierOmen.27568.3 +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: FNST_trad_j
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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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+ # FNST_trad_j
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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: 2.6540
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+ - Accuracy: 0.6525
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+ - F1: 0.6178
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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-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: 32
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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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+ | 1.1058 | 1.0 | 1500 | 1.0564 | 0.5442 | 0.3843 |
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+ | 0.9559 | 2.0 | 3000 | 0.9522 | 0.585 | 0.5503 |
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+ | 0.8789 | 3.0 | 4500 | 0.8843 | 0.61 | 0.5733 |
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+ | 0.8292 | 4.0 | 6000 | 0.8614 | 0.6167 | 0.5734 |
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+ | 0.7807 | 5.0 | 7500 | 0.8519 | 0.62 | 0.5896 |
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+ | 0.7559 | 6.0 | 9000 | 0.8648 | 0.6283 | 0.5965 |
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+ | 0.7098 | 7.0 | 10500 | 0.8579 | 0.63 | 0.5961 |
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+ | 0.6703 | 8.0 | 12000 | 0.8536 | 0.6417 | 0.6029 |
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+ | 0.6114 | 9.0 | 13500 | 0.8686 | 0.6358 | 0.5997 |
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+ | 0.611 | 10.0 | 15000 | 0.8948 | 0.6342 | 0.6045 |
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+ | 0.5614 | 11.0 | 16500 | 0.9173 | 0.6342 | 0.6046 |
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+ | 0.515 | 12.0 | 18000 | 0.9289 | 0.6425 | 0.6089 |
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+ | 0.5107 | 13.0 | 19500 | 0.9581 | 0.64 | 0.6052 |
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+ | 0.4691 | 14.0 | 21000 | 1.0099 | 0.6433 | 0.6091 |
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+ | 0.4476 | 15.0 | 22500 | 1.0543 | 0.6458 | 0.6108 |
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+ | 0.398 | 16.0 | 24000 | 1.1170 | 0.6425 | 0.6051 |
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+ | 0.3828 | 17.0 | 25500 | 1.1585 | 0.6517 | 0.6102 |
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+ | 0.3567 | 18.0 | 27000 | 1.2252 | 0.6475 | 0.6114 |
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+ | 0.3334 | 19.0 | 28500 | 1.2827 | 0.6675 | 0.6317 |
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+ | 0.2982 | 20.0 | 30000 | 1.4256 | 0.6517 | 0.6257 |
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+ | 0.2734 | 21.0 | 31500 | 1.4591 | 0.6583 | 0.6305 |
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+ | 0.2556 | 22.0 | 33000 | 1.5516 | 0.66 | 0.6263 |
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+ | 0.2409 | 23.0 | 34500 | 1.6793 | 0.6592 | 0.6219 |
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+ | 0.2226 | 24.0 | 36000 | 1.8157 | 0.66 | 0.6218 |
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+ | 0.1971 | 25.0 | 37500 | 1.9089 | 0.6575 | 0.6241 |
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+ | 0.1832 | 26.0 | 39000 | 2.0406 | 0.6558 | 0.6300 |
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+ | 0.1921 | 27.0 | 40500 | 2.1448 | 0.6583 | 0.6254 |
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+ | 0.1496 | 28.0 | 42000 | 2.2888 | 0.6458 | 0.6136 |
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+ | 0.1538 | 29.0 | 43500 | 2.3520 | 0.66 | 0.6241 |
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+ | 0.1558 | 30.0 | 45000 | 2.4748 | 0.6492 | 0.6207 |
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+ | 0.1409 | 31.0 | 46500 | 2.5126 | 0.6542 | 0.6175 |
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+ | 0.119 | 32.0 | 48000 | 2.6540 | 0.6525 | 0.6178 |
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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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