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djsull/aha_class_v1

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README.md ADDED
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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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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: aha_class_v1
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+ results: []
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+ ---
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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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+
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+ # aha_class_v1
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+
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+ This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0923
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+ - F1: 0.9620
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+ - Roc Auc: 0.9701
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+ - Accuracy: 0.9391
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 42 | 0.1469 | 0.9620 | 0.9701 | 0.9304 |
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+ | No log | 2.0 | 84 | 0.1095 | 0.9661 | 0.9724 | 0.9478 |
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+ | No log | 3.0 | 126 | 0.1102 | 0.9447 | 0.9553 | 0.9217 |
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+ | No log | 4.0 | 168 | 0.1090 | 0.9536 | 0.9637 | 0.9304 |
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+ | No log | 5.0 | 210 | 0.0923 | 0.9620 | 0.9701 | 0.9391 |
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+ | No log | 6.0 | 252 | 0.1059 | 0.9461 | 0.9613 | 0.9130 |
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+ | No log | 7.0 | 294 | 0.1125 | 0.9620 | 0.9701 | 0.9478 |
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+ | No log | 8.0 | 336 | 0.0942 | 0.9664 | 0.9743 | 0.9478 |
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+ | No log | 9.0 | 378 | 0.0958 | 0.9667 | 0.9763 | 0.9478 |
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+ | No log | 10.0 | 420 | 0.0956 | 0.9705 | 0.9766 | 0.9565 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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