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--- |
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license: mit |
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base_model: Mikask/bdc2024-tpg |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: bdc2024-tpg-2 |
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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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# bdc2024-tpg-2 |
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This model is a fine-tuned version of [Mikask/bdc2024-tpg](https://huggingface.co./Mikask/bdc2024-tpg) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0953 |
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- Accuracy: 0.9825 |
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- Balanced Accuracy: 0.9863 |
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- Precision: 0.9832 |
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- Recall: 0.9825 |
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- F1: 0.9826 |
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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: 6e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:| |
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| 0.0781 | 1.0 | 900 | 0.0990 | 0.9803 | 0.9779 | 0.9810 | 0.9803 | 0.9804 | |
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| 0.0228 | 2.0 | 1800 | 0.0925 | 0.9782 | 0.9752 | 0.9788 | 0.9782 | 0.9782 | |
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| 0.017 | 3.0 | 2700 | 0.0953 | 0.9825 | 0.9863 | 0.9832 | 0.9825 | 0.9826 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.13.3 |
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