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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: answerdotai/ModernBERT-base |
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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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model-index: |
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- name: ModernBERT_wine_quality_reviews_ft |
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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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# ModernBERT_wine_quality_reviews_ft |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8255 |
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- Accuracy: 0.6865 |
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- F1: 0.6873 |
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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: 8e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 1.0765 | 0.1653 | 350 | 0.8973 | 0.5849 | 0.5797 | |
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| 0.848 | 0.3305 | 700 | 0.7721 | 0.6516 | 0.6483 | |
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| 0.7796 | 0.4958 | 1050 | 0.7682 | 0.6466 | 0.6470 | |
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| 0.7671 | 0.6610 | 1400 | 0.7448 | 0.6611 | 0.6566 | |
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| 0.7434 | 0.8263 | 1750 | 0.7378 | 0.6643 | 0.6634 | |
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| 0.7232 | 0.9915 | 2100 | 0.7086 | 0.6789 | 0.6736 | |
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| 0.653 | 1.1568 | 2450 | 0.7150 | 0.6768 | 0.6764 | |
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| 0.6312 | 1.3220 | 2800 | 0.7119 | 0.6785 | 0.6761 | |
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| 0.6298 | 1.4873 | 3150 | 0.6982 | 0.6879 | 0.6843 | |
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| 0.6307 | 1.6525 | 3500 | 0.7072 | 0.6863 | 0.6864 | |
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| 0.6338 | 1.8178 | 3850 | 0.6950 | 0.6862 | 0.6813 | |
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| 0.6252 | 1.9830 | 4200 | 0.6996 | 0.6850 | 0.6853 | |
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| 0.4418 | 2.1483 | 4550 | 0.8353 | 0.6911 | 0.6899 | |
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| 0.4016 | 2.3135 | 4900 | 0.8428 | 0.6825 | 0.6815 | |
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| 0.404 | 2.4788 | 5250 | 0.8241 | 0.6824 | 0.6822 | |
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| 0.404 | 2.6440 | 5600 | 0.8255 | 0.6865 | 0.6873 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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