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--- |
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base_model: klue/roberta-base |
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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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- precision |
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- recall |
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model-index: |
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- name: roberta-base-finetuned-tc |
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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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# roberta-base-finetuned-tc |
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This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5510 |
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- Accuracy: 0.8442 |
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- F1: 0.8376 |
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- Precision: 0.8466 |
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- Recall: 0.8442 |
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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: 128 |
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- eval_batch_size: 128 |
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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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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 15 | 1.3600 | 0.5055 | 0.3395 | 0.2556 | 0.5055 | |
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| No log | 2.0 | 30 | 0.9601 | 0.6712 | 0.5846 | 0.6041 | 0.6712 | |
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| No log | 3.0 | 45 | 0.7381 | 0.7865 | 0.7621 | 0.7439 | 0.7865 | |
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| No log | 4.0 | 60 | 0.6402 | 0.8172 | 0.7964 | 0.7793 | 0.8172 | |
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| No log | 5.0 | 75 | 0.5886 | 0.8258 | 0.8074 | 0.8163 | 0.8258 | |
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| No log | 6.0 | 90 | 0.5714 | 0.8344 | 0.8213 | 0.8280 | 0.8344 | |
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| No log | 7.0 | 105 | 0.5618 | 0.8331 | 0.8233 | 0.8386 | 0.8331 | |
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| No log | 8.0 | 120 | 0.5559 | 0.8380 | 0.8307 | 0.8428 | 0.8380 | |
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| No log | 9.0 | 135 | 0.5510 | 0.8442 | 0.8376 | 0.8466 | 0.8442 | |
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| No log | 10.0 | 150 | 0.5545 | 0.8429 | 0.8355 | 0.8454 | 0.8429 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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