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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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model-index: |
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- name: featured-articles |
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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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# featured-articles |
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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: 1.9620 |
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- Weighted F1: 0.6740 |
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- Accepted Precision: 0.7453 |
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- Accepted Recall: 0.7790 |
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- Accepted F1: 0.7618 |
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- Rejected Precision: 0.5273 |
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- Rejected Recall: 0.4807 |
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- Rejected F1: 0.5029 |
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- Accuracy: 0.6779 |
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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: Use OptimizerNames.ADAMW_TORCH 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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Weighted F1 | Accepted Precision | Accepted Recall | Accepted F1 | Rejected Precision | Rejected Recall | Rejected F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:--------:| |
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| 0.6595 | 1.0 | 267 | 0.6187 | 0.6876 | 0.752 | 0.7989 | 0.7747 | 0.5535 | 0.4862 | 0.5176 | 0.6929 | |
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| 0.4807 | 2.0 | 534 | 0.7625 | 0.5677 | 0.8030 | 0.4504 | 0.5771 | 0.4226 | 0.7845 | 0.5493 | 0.5637 | |
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| 0.3013 | 3.0 | 801 | 1.7444 | 0.6577 | 0.7105 | 0.9178 | 0.8010 | 0.6282 | 0.2707 | 0.3784 | 0.6985 | |
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| 0.0381 | 4.0 | 1068 | 1.9620 | 0.6740 | 0.7453 | 0.7790 | 0.7618 | 0.5273 | 0.4807 | 0.5029 | 0.6779 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.2.2 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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