| | ---
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| | library_name: transformers
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| | base_model: dccuchile/albert-base-spanish
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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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| | model-index:
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| | - name: mi-super-modelo
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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
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
|
| | # mi-super-modelo
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| |
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| | This model is a fine-tuned version of [dccuchile/albert-base-spanish](https://huggingface.co/dccuchile/albert-base-spanish) on the None dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 1.5146
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| | - Accuracy: 0.38
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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: 5e-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: 1
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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 |
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| | |:-------------:|:------:|:----:|:---------------:|:--------:|
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| | | 1.7601 | 0.0455 | 2 | 1.7148 | 0.3333 |
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| | | 1.7063 | 0.0909 | 4 | 1.6888 | 0.3 |
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| | | 1.5512 | 0.1364 | 6 | 1.6585 | 0.2933 |
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| | | 1.5312 | 0.1818 | 8 | 1.6514 | 0.3 |
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| | | 1.5006 | 0.2273 | 10 | 1.6581 | 0.3 |
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| | | 1.6519 | 0.2727 | 12 | 1.6511 | 0.3067 |
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| | | 1.6397 | 0.3182 | 14 | 1.6347 | 0.3 |
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| | | 1.5275 | 0.3636 | 16 | 1.6183 | 0.3067 |
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| | | 1.8253 | 0.4091 | 18 | 1.5949 | 0.3 |
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| | | 1.7725 | 0.4545 | 20 | 1.5708 | 0.3 |
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| | | 1.5334 | 0.5 | 22 | 1.5591 | 0.3067 |
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| | | 1.3062 | 0.5455 | 24 | 1.5535 | 0.3133 |
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| | | 1.4629 | 0.5909 | 26 | 1.5459 | 0.32 |
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| | | 1.5431 | 0.6364 | 28 | 1.5408 | 0.3333 |
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| | | 1.62 | 0.6818 | 30 | 1.5355 | 0.36 |
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| | | 1.4165 | 0.7273 | 32 | 1.5299 | 0.36 |
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| | | 1.6135 | 0.7727 | 34 | 1.5244 | 0.3733 |
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| | | 1.5181 | 0.8182 | 36 | 1.5220 | 0.3733 |
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| | | 1.3877 | 0.8636 | 38 | 1.5196 | 0.3733 |
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| | | 1.6638 | 0.9091 | 40 | 1.5174 | 0.3733 |
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| | | 1.4348 | 0.9545 | 42 | 1.5154 | 0.38 |
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| | | 1.4226 | 1.0 | 44 | 1.5146 | 0.38 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.45.2
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| | - Pytorch 2.5.0
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| | - Datasets 3.1.0
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| | - Tokenizers 0.20.1
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| |
|
