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--- |
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license: cc-by-4.0 |
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base_model: bertin-project/bertin-roberta-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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: my-model-Bertin-Area |
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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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# my-model-Bertin-Area |
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This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0081 |
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- Accuracy: 0.5540 |
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- F1: 0.5447 |
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- Precision: 0.6083 |
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- Recall: 0.5540 |
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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: 5e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 5 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.8057 | 1.0 | 22 | 1.6694 | 0.3094 | 0.1478 | 0.0971 | 0.3094 | |
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| 1.6881 | 2.0 | 44 | 1.5645 | 0.3741 | 0.2735 | 0.2381 | 0.3741 | |
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| 1.4559 | 3.0 | 66 | 1.3527 | 0.5612 | 0.4682 | 0.4308 | 0.5612 | |
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| 1.0349 | 4.0 | 88 | 1.2698 | 0.5108 | 0.4710 | 0.5251 | 0.5108 | |
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| 0.5922 | 5.0 | 110 | 1.3228 | 0.5396 | 0.5357 | 0.5761 | 0.5396 | |
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| 0.3388 | 6.0 | 132 | 1.3421 | 0.5324 | 0.5465 | 0.6025 | 0.5324 | |
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| 0.1581 | 7.0 | 154 | 1.6898 | 0.5396 | 0.5210 | 0.6214 | 0.5396 | |
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| 0.0756 | 8.0 | 176 | 1.5726 | 0.5971 | 0.5805 | 0.5852 | 0.5971 | |
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| 0.0485 | 9.0 | 198 | 1.6224 | 0.5971 | 0.6071 | 0.6341 | 0.5971 | |
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| 0.0238 | 10.0 | 220 | 1.9468 | 0.5683 | 0.5592 | 0.6588 | 0.5683 | |
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| 0.0111 | 11.0 | 242 | 1.8085 | 0.5540 | 0.5505 | 0.5994 | 0.5540 | |
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| 0.0043 | 12.0 | 264 | 1.7379 | 0.5755 | 0.5672 | 0.6076 | 0.5755 | |
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| 0.0029 | 13.0 | 286 | 1.9594 | 0.5612 | 0.5527 | 0.6202 | 0.5612 | |
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| 0.0024 | 14.0 | 308 | 2.0399 | 0.5683 | 0.5606 | 0.6429 | 0.5683 | |
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| 0.0021 | 15.0 | 330 | 1.9871 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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| 0.002 | 16.0 | 352 | 1.9870 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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| 0.0018 | 17.0 | 374 | 1.9927 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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| 0.0018 | 18.0 | 396 | 2.0027 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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| 0.0017 | 19.0 | 418 | 2.0077 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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| 0.0017 | 20.0 | 440 | 2.0081 | 0.5540 | 0.5447 | 0.6083 | 0.5540 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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