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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: group2_non_all_zero
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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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# group2_non_all_zero
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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: 0.3907
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- Precision: 0.0415
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- Recall: 0.086
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- F1: 0.0560
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- Accuracy: 0.9044
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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: 8
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- eval_batch_size: 8
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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: 6
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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 | 172 | 0.2512 | 0.0608 | 0.044 | 0.0510 | 0.9439 |
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| No log | 2.0 | 344 | 0.2667 | 0.0355 | 0.048 | 0.0408 | 0.9194 |
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| 0.4561 | 3.0 | 516 | 0.2883 | 0.0445 | 0.078 | 0.0566 | 0.9198 |
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| 0.4561 | 4.0 | 688 | 0.3610 | 0.0379 | 0.092 | 0.0537 | 0.8968 |
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| 0.4561 | 5.0 | 860 | 0.3840 | 0.0528 | 0.094 | 0.0676 | 0.9095 |
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| 0.1508 | 6.0 | 1032 | 0.3907 | 0.0415 | 0.086 | 0.0560 | 0.9044 |
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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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