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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_h
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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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# ABL_trad_h
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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: 1.3621
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- Accuracy: 0.6867
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- F1: 0.6845
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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: 12
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- eval_batch_size: 12
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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: 24
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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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| 1.0316 | 1.0 | 1000 | 0.9725 | 0.5383 | 0.5182 |
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| 0.8887 | 2.0 | 2000 | 0.8652 | 0.5925 | 0.5901 |
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| 0.8132 | 3.0 | 3000 | 0.8327 | 0.6175 | 0.6143 |
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| 0.7639 | 4.0 | 4000 | 0.8030 | 0.6367 | 0.6356 |
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| 0.7233 | 5.0 | 5000 | 0.7969 | 0.6433 | 0.6408 |
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| 0.6977 | 6.0 | 6000 | 0.7848 | 0.6508 | 0.6500 |
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| 0.6531 | 7.0 | 7000 | 0.7923 | 0.66 | 0.6590 |
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| 0.6149 | 8.0 | 8000 | 0.7879 | 0.6683 | 0.6667 |
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| 0.5964 | 9.0 | 9000 | 0.7835 | 0.6708 | 0.6705 |
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| 0.5508 | 10.0 | 10000 | 0.8072 | 0.6725 | 0.6701 |
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| 0.5288 | 11.0 | 11000 | 0.8277 | 0.665 | 0.6604 |
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| 0.4828 | 12.0 | 12000 | 0.8436 | 0.6833 | 0.6810 |
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| 0.4457 | 13.0 | 13000 | 0.8679 | 0.6717 | 0.6681 |
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| 0.432 | 14.0 | 14000 | 0.8695 | 0.6692 | 0.6679 |
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| 0.4128 | 15.0 | 15000 | 0.9217 | 0.6858 | 0.6833 |
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| 0.3831 | 16.0 | 16000 | 0.9300 | 0.6733 | 0.6714 |
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| 0.3471 | 17.0 | 17000 | 0.9796 | 0.675 | 0.6726 |
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| 0.3245 | 18.0 | 18000 | 1.0319 | 0.6742 | 0.6726 |
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| 0.3016 | 19.0 | 19000 | 1.0977 | 0.6733 | 0.6692 |
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| 0.2702 | 20.0 | 20000 | 1.1130 | 0.6667 | 0.6634 |
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| 0.2602 | 21.0 | 21000 | 1.1475 | 0.6758 | 0.6741 |
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| 0.2316 | 22.0 | 22000 | 1.2237 | 0.6725 | 0.6694 |
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| 0.2176 | 23.0 | 23000 | 1.2664 | 0.6775 | 0.6758 |
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| 0.2067 | 24.0 | 24000 | 1.3621 | 0.6867 | 0.6845 |
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### Framework versions
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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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