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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: 3.1711 |
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- Accuracy: 0.4903 |
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- F1: 0.4767 |
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- Precision: 0.5366 |
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- Recall: 0.4903 |
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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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| 1.8349 | 1.0 | 25 | 1.7703 | 0.3032 | 0.2608 | 0.2991 | 0.3032 | |
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| 1.7709 | 2.0 | 50 | 1.7153 | 0.3355 | 0.2347 | 0.2079 | 0.3355 | |
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| 1.7315 | 3.0 | 75 | 1.6515 | 0.3613 | 0.2934 | 0.2937 | 0.3613 | |
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| 1.596 | 4.0 | 100 | 1.6332 | 0.3871 | 0.3405 | 0.3123 | 0.3871 | |
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| 1.3388 | 5.0 | 125 | 1.6449 | 0.4065 | 0.3298 | 0.2900 | 0.4065 | |
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| 1.0783 | 6.0 | 150 | 1.5722 | 0.4581 | 0.3797 | 0.3760 | 0.4581 | |
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| 0.8663 | 7.0 | 175 | 1.6593 | 0.3935 | 0.3563 | 0.3490 | 0.3935 | |
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| 0.6118 | 8.0 | 200 | 1.9177 | 0.4581 | 0.4481 | 0.4658 | 0.4581 | |
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| 0.4206 | 9.0 | 225 | 2.2944 | 0.4065 | 0.3920 | 0.4286 | 0.4065 | |
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| 0.3375 | 10.0 | 250 | 2.2870 | 0.4387 | 0.4359 | 0.4889 | 0.4387 | |
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| 0.2334 | 11.0 | 275 | 2.4912 | 0.4065 | 0.4015 | 0.4546 | 0.4065 | |
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| 0.1618 | 12.0 | 300 | 2.5429 | 0.4710 | 0.4499 | 0.5204 | 0.4710 | |
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| 0.1238 | 13.0 | 325 | 2.7109 | 0.4710 | 0.4458 | 0.5135 | 0.4710 | |
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| 0.0906 | 14.0 | 350 | 2.8377 | 0.4774 | 0.4594 | 0.5092 | 0.4774 | |
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| 0.071 | 15.0 | 375 | 3.0123 | 0.4839 | 0.4656 | 0.5461 | 0.4839 | |
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| 0.0498 | 16.0 | 400 | 3.0204 | 0.4710 | 0.4517 | 0.4959 | 0.4710 | |
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| 0.0416 | 17.0 | 425 | 3.0939 | 0.4839 | 0.4622 | 0.5107 | 0.4839 | |
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| 0.0281 | 18.0 | 450 | 3.0979 | 0.4903 | 0.4793 | 0.5281 | 0.4903 | |
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| 0.0226 | 19.0 | 475 | 3.1622 | 0.4839 | 0.4708 | 0.5202 | 0.4839 | |
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| 0.0185 | 20.0 | 500 | 3.1711 | 0.4903 | 0.4767 | 0.5366 | 0.4903 | |
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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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