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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/roberta-base
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tags:
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- generated_from_trainer
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model-index:
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- name: unique-gnu-764
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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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# unique-gnu-764
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1730
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- Hamming Loss: 0.0606
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- Zero One Loss: 0.485
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- Jaccard Score: 0.4424
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- Hamming Loss Optimised: 0.059
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- Hamming Loss Threshold: 0.5979
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- Zero One Loss Optimised: 0.4225
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- Zero One Loss Threshold: 0.3775
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- Jaccard Score Optimised: 0.3443
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- Jaccard Score Threshold: 0.2391
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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: 9.099061382218765e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 2024
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 2
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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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| 0.3041 | 1.0 | 800 | 0.2106 | 0.0741 | 0.6013 | 0.5782 | 0.0751 | 0.6394 | 0.495 | 0.3884 | 0.4128 | 0.2790 |
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| 0.181 | 2.0 | 1600 | 0.1730 | 0.0606 | 0.485 | 0.4424 | 0.059 | 0.5979 | 0.4225 | 0.3775 | 0.3443 | 0.2391 |
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### Framework versions
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- Transformers 4.47.0
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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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