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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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model-index:
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- name: bright-loon-253
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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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# bright-loon-253
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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: 0.1606
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- Hamming Loss: 0.0575
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- Zero One Loss: 0.3938
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- Jaccard Score: 0.3426
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- Hamming Loss Optimised: 0.056
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- Hamming Loss Threshold: 0.7152
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- Zero One Loss Optimised: 0.3962
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- Zero One Loss Threshold: 0.4832
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- Jaccard Score Optimised: 0.3179
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- Jaccard Score Threshold: 0.2879
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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: 4.6017800734322744e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 2024
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9392111443474531,0.8944286688071013) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
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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 | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
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| No log | 1.0 | 100 | 0.1583 | 0.0599 | 0.4775 | 0.4292 | 0.0594 | 0.5609 | 0.4425 | 0.3912 | 0.3408 | 0.2948 |
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| No log | 2.0 | 200 | 0.1515 | 0.0556 | 0.4075 | 0.3553 | 0.0566 | 0.7821 | 0.4 | 0.4285 | 0.3200 | 0.2934 |
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| No log | 3.0 | 300 | 0.1606 | 0.0575 | 0.3938 | 0.3426 | 0.056 | 0.7152 | 0.3962 | 0.4832 | 0.3179 | 0.2879 |
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.21.0
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