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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: nickprock/setfit-italian-hate-speech |
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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-baseline-it |
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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-baseline-it |
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This model is a fine-tuned version of [nickprock/setfit-italian-hate-speech](https://huggingface.co/nickprock/setfit-italian-hate-speech) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6297 |
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- Accuracy: 0.9325 |
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- F1: 0.8831 |
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- Precision: 0.9131 |
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- Recall: 0.8596 |
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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: 150 |
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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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| 0.4607 | 1.0 | 95 | 0.3423 | 0.9264 | 0.8742 | 0.8965 | 0.8558 | |
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| 0.2351 | 2.0 | 190 | 0.4198 | 0.9325 | 0.8831 | 0.9131 | 0.8596 | |
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| 0.201 | 3.0 | 285 | 0.1992 | 0.9632 | 0.9430 | 0.9247 | 0.9649 | |
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| 0.1004 | 4.0 | 380 | 0.4917 | 0.9202 | 0.8535 | 0.9155 | 0.8150 | |
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| 0.1 | 5.0 | 475 | 0.3548 | 0.9387 | 0.8979 | 0.9086 | 0.8881 | |
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| 0.0438 | 6.0 | 570 | 0.6297 | 0.9325 | 0.8831 | 0.9131 | 0.8596 | |
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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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