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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-large |
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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_large_Assign_4 |
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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_large_Assign_4 |
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1879 |
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- Accuracy: 0.9668 |
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- F1: 0.9664 |
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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: 4e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: cosine |
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- num_epochs: 8 |
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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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| 0.9447 | 0.8386 | 400 | 0.2952 | 0.9387 | 0.9358 | |
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| 0.0999 | 1.6771 | 800 | 0.2098 | 0.9513 | 0.9506 | |
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| 0.0582 | 2.5157 | 1200 | 0.2062 | 0.9574 | 0.9570 | |
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| 0.0185 | 3.3543 | 1600 | 0.1982 | 0.9635 | 0.9629 | |
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| 0.011 | 4.1929 | 2000 | 0.2009 | 0.9639 | 0.9632 | |
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| 0.0044 | 5.0314 | 2400 | 0.1852 | 0.9671 | 0.9668 | |
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| 0.0022 | 5.8700 | 2800 | 0.1915 | 0.9665 | 0.9661 | |
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| 0.0009 | 6.7086 | 3200 | 0.1878 | 0.9665 | 0.9661 | |
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| 0.0002 | 7.5472 | 3600 | 0.1879 | 0.9668 | 0.9664 | |
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### Framework versions |
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- Transformers 4.56.2 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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