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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: distilbert/distilbert-base-cased
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tags:
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- generated_from_trainer
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model-index:
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- name: popular-snail-470
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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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# popular-snail-470
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This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1428
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- Hamming Loss: 0.0394
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- Zero One Loss: 0.8140
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- Jaccard Score: 0.7792
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- Hamming Loss Optimised: 0.0378
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- Hamming Loss Threshold: 0.2878
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- Zero One Loss Optimised: 0.71
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- Zero One Loss Threshold: 0.1741
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- Jaccard Score Optimised: 0.6376
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- Jaccard Score Threshold: 0.1616
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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: 5.0943791435964314e-05
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- train_batch_size: 20
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- eval_batch_size: 20
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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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| No log | 1.0 | 160 | 0.1685 | 0.0438 | 0.8812 | 0.8679 | 0.0438 | 0.5944 | 0.8812 | 0.7111 | 0.8679 | 0.7111 |
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| No log | 2.0 | 320 | 0.1422 | 0.0398 | 0.815 | 0.7804 | 0.0363 | 0.2166 | 0.6925 | 0.1817 | 0.621 | 0.1587 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu118
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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