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README.md
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---
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license: cc-by-sa-4.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: deberta-v2-base-japanese-detect-ai
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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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# deberta-v2-base-japanese-detect-ai
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This model is a fine-tuned version of [ku-nlp/deberta-v2-base-japanese](https://huggingface.co/ku-nlp/deberta-v2-base-japanese) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1032
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- Accuracy: 0.9842
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- F1: 0.9842
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.0409 | 1.0 | 403 | 0.1045 | 0.9823 | 0.9823 |
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| 0.0101 | 2.0 | 806 | 0.0567 | 0.9893 | 0.9893 |
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| 0.0008 | 3.0 | 1209 | 0.1032 | 0.9842 | 0.9842 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.0+cu113
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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