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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: victorious-moose-736
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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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# victorious-moose-736
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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: 0.1689
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- Hamming Loss: 0.0619
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- Zero One Loss: 0.4450
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- Jaccard Score: 0.3857
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- Hamming Loss Optimised: 0.0592
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- Hamming Loss Threshold: 0.7299
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- Zero One Loss Optimised: 0.4387
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- Zero One Loss Threshold: 0.4119
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- Jaccard Score Optimised: 0.3464
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- Jaccard Score Threshold: 0.2462
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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: 2.115467719563917e-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=(0.8101446041573426,0.9056914031952074) 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: 4
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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 | 0.1830 | 0.0644 | 0.5162 | 0.4740 | 0.0643 | 0.4982 | 0.4975 | 0.3276 | 0.3889 | 0.2962 |
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| No log | 2.0 | 200 | 0.1643 | 0.062 | 0.4625 | 0.3920 | 0.0597 | 0.6455 | 0.4587 | 0.4816 | 0.3518 | 0.2755 |
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| No log | 3.0 | 300 | 0.1678 | 0.0636 | 0.4550 | 0.3934 | 0.0595 | 0.7017 | 0.4425 | 0.3683 | 0.3441 | 0.2888 |
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| No log | 4.0 | 400 | 0.1689 | 0.0619 | 0.4450 | 0.3857 | 0.0592 | 0.7299 | 0.4387 | 0.4119 | 0.3464 | 0.2462 |
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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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