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---
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library_name: peft
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license: mit
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base_model: microsoft/deberta-v3-small
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tags:
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- generated_from_trainer
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model-index:
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- name: valuable-auk-490
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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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# valuable-auk-490 |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4671 |
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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: 0.5944 |
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- Zero One Loss Optimised: 0.7662 |
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- Zero One Loss Threshold: 0.4039 |
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- Jaccard Score Optimised: 0.7638 |
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- Jaccard Score Threshold: 0.4056 |
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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: 6.612534950619908e-06 |
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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: 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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| 0.6856 | 1.0 | 800 | 0.6690 | 0.3683 | 1.0 | 0.9304 | 0.1123 | 0.6927 | 0.9613 | 0.5584 | 0.8878 | 0.2889 | |
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| 0.5765 | 2.0 | 1600 | 0.5081 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.5944 | 1.0 | 0.9000 | 0.8559 | 0.4056 | |
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| 0.5242 | 3.0 | 2400 | 0.4754 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.5944 | 0.7662 | 0.4143 | 0.7638 | 0.4124 | |
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| 0.4923 | 4.0 | 3200 | 0.4671 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.5944 | 0.7662 | 0.4039 | 0.7638 | 0.4056 | |
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### Framework versions |
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- PEFT 0.13.2 |
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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 |
