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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: dazzling-hound-586
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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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# dazzling-hound-586
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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: 0.2093
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- Hamming Loss: 0.0755
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- Zero One Loss: 0.6188
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- Jaccard Score: 0.5985
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- Hamming Loss Optimised: 0.075
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- Hamming Loss Threshold: 0.4882
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- Zero One Loss Optimised: 0.5513
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- Zero One Loss Threshold: 0.2887
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- Jaccard Score Optimised: 0.4541
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- Jaccard Score Threshold: 0.2220
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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: 5.871069949578436e-06
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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=(0.8955773174153844,0.9360886643830869) 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 | 0.2884 | 0.0989 | 0.8588 | 0.8569 | 0.0953 | 0.3770 | 0.7338 | 0.2090 | 0.6634 | 0.1684 |
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| No log | 2.0 | 200 | 0.2256 | 0.0801 | 0.6700 | 0.6558 | 0.0783 | 0.4253 | 0.5713 | 0.2674 | 0.4899 | 0.2186 |
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| No log | 3.0 | 300 | 0.2093 | 0.0755 | 0.6188 | 0.5985 | 0.075 | 0.4882 | 0.5513 | 0.2887 | 0.4541 | 0.2220 |
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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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