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---
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library_name: transformers
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license: mit
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base_model: microsoft/deberta-v3-xsmall
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tags:
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- generated_from_trainer
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model-index:
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- name: resilient-rook-798
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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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# resilient-rook-798
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This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2372
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- Hamming Loss: 0.0925
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- Zero One Loss: 0.7925
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- Jaccard Score: 0.79
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- Hamming Loss Optimised: 0.0789
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- Hamming Loss Threshold: 0.3524
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- Zero One Loss Optimised: 0.5887
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- Zero One Loss Threshold: 0.3038
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- Jaccard Score Optimised: 0.5148
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- Jaccard Score Threshold: 0.2378
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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: 32
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- eval_batch_size: 32
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- seed: 2024
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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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| 0.4118 | 1.0 | 100 | 0.3355 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
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| 0.308 | 2.0 | 200 | 0.2855 | 0.0938 | 0.8125 | 0.81 | 0.0929 | 0.3525 | 0.7488 | 0.1661 | 0.6086 | 0.1537 |
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| 0.2668 | 3.0 | 300 | 0.2478 | 0.0925 | 0.7913 | 0.7888 | 0.0865 | 0.3723 | 0.64 | 0.2728 | 0.5209 | 0.1919 |
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| 0.2417 | 4.0 | 400 | 0.2372 | 0.0925 | 0.7925 | 0.79 | 0.0789 | 0.3524 | 0.5887 | 0.3038 | 0.5148 | 0.2378 |
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### Framework versions
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- Transformers 4.45.1
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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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