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--- |
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license: apache-2.0 |
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base_model: indolem/indobertweet-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: classification-hate-speech-DE |
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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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# classification-hate-speech-DE |
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This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6475 |
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- F1 macro: 0.3742 |
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- Weighted: 0.5772 |
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- Balanced accuracy: 0.4995 |
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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: 3e-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: 11 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:| |
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| 1.3987 | 1.0 | 152 | 1.1932 | 0.3716 | 0.6024 | 0.4578 | |
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| 0.8176 | 2.0 | 304 | 1.1670 | 0.4016 | 0.6136 | 0.4964 | |
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| 0.6289 | 3.0 | 456 | 1.2036 | 0.4099 | 0.6391 | 0.5131 | |
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| 0.1606 | 4.0 | 608 | 1.7535 | 0.3725 | 0.5728 | 0.5006 | |
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| 0.0285 | 5.0 | 760 | 1.8911 | 0.4152 | 0.6312 | 0.5199 | |
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| 0.0693 | 6.0 | 912 | 2.1700 | 0.4018 | 0.6026 | 0.5087 | |
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| 0.0047 | 7.0 | 1064 | 2.2234 | 0.3929 | 0.6128 | 0.5061 | |
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| 0.0032 | 8.0 | 1216 | 2.5087 | 0.3759 | 0.5816 | 0.4993 | |
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| 0.0025 | 9.0 | 1368 | 2.7507 | 0.3823 | 0.5547 | 0.5173 | |
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| 0.0016 | 10.0 | 1520 | 2.6432 | 0.3758 | 0.5808 | 0.5002 | |
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| 0.0012 | 11.0 | 1672 | 2.6475 | 0.3742 | 0.5772 | 0.4995 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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