| ---
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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: lyrical-grouse-303
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| results: []
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| ---
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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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|
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| # lyrical-grouse-303
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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: 0.3514
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| - Hamming Loss: 0.1123
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| - Zero One Loss: 1.0
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| - Jaccard Score: 1.0
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| - Hamming Loss Optimised: 0.1123
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| - Hamming Loss Threshold: 0.9000
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| - Zero One Loss Optimised: 1.0
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| - Zero One Loss Threshold: 0.9000
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| - Jaccard Score Optimised: 1.0
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| - Jaccard Score Threshold: 0.9000
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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: 64
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| - eval_batch_size: 64
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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: 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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| | 0.5032 | 1.0 | 50 | 0.3816 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
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| | 0.3685 | 2.0 | 100 | 0.3514 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
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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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