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yooonsangbeom
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bert-base-finetuned-ynat

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +16 -15
  2. pytorch_model.bin +1 -1
README.md CHANGED
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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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  datasets:
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  - klue
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  metrics:
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- - f1
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  model-index:
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  - name: bert-base-finetuned-ynat
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  results:
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  split: validation
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  args: ynat
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  metrics:
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- - name: F1
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- type: f1
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- value: 0.8696415258442162
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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
@@ -31,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3642
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- - F1: 0.8696
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 90 | 0.4440 | 0.8502 |
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- | No log | 2.0 | 180 | 0.3793 | 0.8667 |
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- | No log | 3.0 | 270 | 0.3642 | 0.8696 |
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- | No log | 4.0 | 360 | 0.3664 | 0.8693 |
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- | No log | 5.0 | 450 | 0.3675 | 0.8689 |
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  ### Framework versions
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- - Transformers 4.30.2
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  - Pytorch 2.0.1+cu117
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  - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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  ---
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  license: cc-by-sa-4.0
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+ base_model: klue/bert-base
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  tags:
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  - generated_from_trainer
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  datasets:
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  - klue
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  metrics:
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+ - accuracy
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  model-index:
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  - name: bert-base-finetuned-ynat
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  results:
 
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  split: validation
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  args: ynat
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  metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8659273086636653
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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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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3691
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+ - Accuracy: 0.8659
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 90 | 0.4090 | 0.8599 |
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+ | No log | 2.0 | 180 | 0.3929 | 0.8578 |
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+ | No log | 3.0 | 270 | 0.3703 | 0.8648 |
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+ | No log | 4.0 | 360 | 0.3714 | 0.8631 |
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+ | No log | 5.0 | 450 | 0.3691 | 0.8659 |
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  ### Framework versions
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+ - Transformers 4.34.0
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  - Pytorch 2.0.1+cu117
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  - Datasets 2.13.1
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+ - Tokenizers 0.14.1
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