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update model card README.md
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: group3_non_all_zero_notEqualWeights
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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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# group3_non_all_zero_notEqualWeights
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3167
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- Precision: 0.0476
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- Recall: 0.2642
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- F1: 0.0807
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- Accuracy: 0.9145
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 55 | 1.3844 | 0.0068 | 0.2579 | 0.0133 | 0.6506 |
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| No log | 2.0 | 110 | 1.1245 | 0.0107 | 0.2342 | 0.0205 | 0.7285 |
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| No log | 3.0 | 165 | 1.2261 | 0.0103 | 0.2120 | 0.0196 | 0.7286 |
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| No log | 4.0 | 220 | 1.1828 | 0.0099 | 0.1693 | 0.0188 | 0.7551 |
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| No log | 5.0 | 275 | 1.2474 | 0.0141 | 0.2152 | 0.0265 | 0.8008 |
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| No log | 6.0 | 330 | 1.4395 | 0.0264 | 0.2516 | 0.0478 | 0.8601 |
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| No log | 7.0 | 385 | 1.5667 | 0.0253 | 0.2278 | 0.0456 | 0.8614 |
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| No log | 8.0 | 440 | 1.6080 | 0.0286 | 0.2468 | 0.0512 | 0.8756 |
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| No log | 9.0 | 495 | 1.7798 | 0.0289 | 0.2358 | 0.0515 | 0.8849 |
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| 0.6462 | 10.0 | 550 | 1.9265 | 0.0364 | 0.2579 | 0.0638 | 0.8933 |
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| 0.6462 | 11.0 | 605 | 2.0633 | 0.0347 | 0.2468 | 0.0608 | 0.8911 |
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| 0.6462 | 12.0 | 660 | 2.2610 | 0.0458 | 0.2690 | 0.0783 | 0.9138 |
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| 0.6462 | 13.0 | 715 | 2.1700 | 0.0435 | 0.2595 | 0.0745 | 0.9044 |
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| 0.6462 | 14.0 | 770 | 2.3153 | 0.0480 | 0.2690 | 0.0814 | 0.9127 |
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| 0.6462 | 15.0 | 825 | 2.3167 | 0.0476 | 0.2642 | 0.0807 | 0.9145 |
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### Framework versions
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- Transformers 4.30.0
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.0
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- Tokenizers 0.13.3
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