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--- |
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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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model-index: |
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- name: sentiment_roberta_large_with_diary |
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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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# sentiment_roberta_large_with_diary |
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This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5671 |
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- Micro f1 score: 80.0000 |
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- Auprc: 77.0282 |
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- Accuracy: 0.8 |
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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: 1e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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_ratio: 0.1 |
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- num_epochs: 1.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro f1 score | Auprc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-------:|:--------:| |
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| 1.6198 | 0.13 | 100 | 1.3872 | 48.9362 | 55.5743 | 0.4894 | |
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| 0.6603 | 0.26 | 200 | 0.9249 | 65.9574 | 62.8759 | 0.6596 | |
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| 0.5387 | 0.4 | 300 | 0.7262 | 73.1915 | 71.1936 | 0.7319 | |
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| 0.4801 | 0.53 | 400 | 0.6623 | 74.0426 | 68.8606 | 0.7404 | |
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| 0.4597 | 0.66 | 500 | 0.6092 | 76.1702 | 75.7346 | 0.7617 | |
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| 0.4217 | 0.79 | 600 | 0.5929 | 78.7234 | 76.8709 | 0.7872 | |
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| 0.4148 | 0.93 | 700 | 0.5671 | 80.0000 | 77.0282 | 0.8 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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