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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: group4_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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# group4_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: 1.2820
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- Precision: 0.0006
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- Recall: 0.08
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- F1: 0.0012
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- Accuracy: 0.4380
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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 | 5 | 2.1670 | 0.0 | 0.0 | 0.0 | 0.0084 |
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| No log | 2.0 | 10 | 2.3289 | 0.0 | 0.0 | 0.0 | 0.0078 |
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| No log | 3.0 | 15 | 2.3316 | 0.0 | 0.0 | 0.0 | 0.0078 |
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| No log | 4.0 | 20 | 2.0441 | 0.0 | 0.0 | 0.0 | 0.0078 |
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| No log | 5.0 | 25 | 2.4322 | 0.0 | 0.0 | 0.0 | 0.0078 |
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| No log | 6.0 | 30 | 1.7898 | 0.0 | 0.0 | 0.0 | 0.0106 |
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| No log | 7.0 | 35 | 1.8590 | 0.0002 | 0.0133 | 0.0004 | 0.0104 |
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| No log | 8.0 | 40 | 1.7022 | 0.0002 | 0.0133 | 0.0004 | 0.0250 |
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| No log | 9.0 | 45 | 1.5775 | 0.0004 | 0.04 | 0.0007 | 0.1004 |
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| No log | 10.0 | 50 | 1.4837 | 0.0006 | 0.08 | 0.0011 | 0.1939 |
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| No log | 11.0 | 55 | 1.3180 | 0.0004 | 0.0533 | 0.0008 | 0.3309 |
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| No log | 12.0 | 60 | 1.3418 | 0.0005 | 0.0667 | 0.0011 | 0.3799 |
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| No log | 13.0 | 65 | 1.3140 | 0.0005 | 0.0667 | 0.0010 | 0.4117 |
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| No log | 14.0 | 70 | 1.3444 | 0.0004 | 0.0533 | 0.0008 | 0.4048 |
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| No log | 15.0 | 75 | 1.2820 | 0.0006 | 0.08 | 0.0012 | 0.4380 |
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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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