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--- |
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library_name: transformers |
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base_model: cardiffnlp/twitter-xlm-roberta-base-hate-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: MultiPRIDE-DualEncoder-LPFT-es |
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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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# MultiPRIDE-DualEncoder-LPFT-es |
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-hate-spanish](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-hate-spanish) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6249 |
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- Accuracy: 0.8030 |
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- F1: 0.4583 |
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- Precision: 0.3929 |
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- Recall: 0.55 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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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| 0.6889 | 1.0 | 77 | 0.6662 | 0.6667 | 0.3333 | 0.2391 | 0.55 | |
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| 0.6354 | 2.0 | 154 | 0.6400 | 0.7879 | 0.2632 | 0.2778 | 0.25 | |
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| 0.6131 | 3.0 | 231 | 0.6525 | 0.8409 | 0.2759 | 0.4444 | 0.2 | |
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| 0.5588 | 4.0 | 308 | 0.6100 | 0.8030 | 0.4091 | 0.375 | 0.45 | |
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| 0.4774 | 5.0 | 385 | 0.6230 | 0.8106 | 0.4444 | 0.4 | 0.5 | |
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| 0.4569 | 6.0 | 462 | 0.6283 | 0.8106 | 0.4681 | 0.4074 | 0.55 | |
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| 0.4519 | 7.0 | 539 | 0.6239 | 0.8030 | 0.4583 | 0.3929 | 0.55 | |
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| 0.4671 | 8.0 | 616 | 0.6284 | 0.8106 | 0.4681 | 0.4074 | 0.55 | |
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| 0.4231 | 9.0 | 693 | 0.6249 | 0.8030 | 0.4583 | 0.3929 | 0.55 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.9.1+cu128 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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