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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: upset-auk-708
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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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# upset-auk-708
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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: 0.3263
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- Hamming Loss: 0.1113
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- Zero One Loss: 0.9875
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- Jaccard Score: 0.9869
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- Hamming Loss Optimised: 0.1077
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- Hamming Loss Threshold: 0.3523
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- Zero One Loss Optimised: 0.785
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- Zero One Loss Threshold: 0.2199
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- Jaccard Score Optimised: 0.7435
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- Jaccard Score Threshold: 0.2046
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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: 1.090012056785563e-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=(0.9422410857324217,0.913862773872536) 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 | 0.4186 | 0.1174 | 0.9862 | 0.9842 | 0.1123 | 0.7028 | 0.9275 | 0.3569 | 0.8325 | 0.3103 |
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| No log | 2.0 | 200 | 0.3414 | 0.1125 | 0.9988 | 0.9988 | 0.1123 | 0.5944 | 0.8362 | 0.2346 | 0.7740 | 0.2016 |
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| No log | 3.0 | 300 | 0.3295 | 0.1116 | 0.9912 | 0.9912 | 0.1091 | 0.3329 | 0.7875 | 0.2167 | 0.7499 | 0.2120 |
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| No log | 4.0 | 400 | 0.3263 | 0.1113 | 0.9875 | 0.9869 | 0.1077 | 0.3523 | 0.785 | 0.2199 | 0.7435 | 0.2046 |
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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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