| | ---
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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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| | model-index:
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| | - name: roberta-interview-intent-f
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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
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
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| | # roberta-interview-intent-f
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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 the None dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 1.9555
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| | - Accuracy: 0.6763
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| | - Macro F1: 0.4521
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| | - Weighted F1: 0.6773
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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: 5e-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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| | - lr_scheduler_warmup_ratio: 0.06
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| | - num_epochs: 8
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| | - mixed_precision_training: Native AMP
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 |
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| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
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| | | 1.4857 | 1.0 | 859 | 1.4013 | 0.6564 | 0.3414 | 0.6440 |
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| | | 0.6763 | 2.0 | 1718 | 1.3329 | 0.6673 | 0.4038 | 0.6551 |
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| | | 0.4559 | 3.0 | 2577 | 1.4175 | 0.6654 | 0.4042 | 0.6653 |
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| | | 0.2971 | 4.0 | 3436 | 1.5689 | 0.6622 | 0.4170 | 0.6637 |
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| | | 0.1885 | 5.0 | 4295 | 1.6916 | 0.6656 | 0.4249 | 0.6694 |
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| | | 0.1181 | 6.0 | 5154 | 1.8043 | 0.6763 | 0.4374 | 0.6713 |
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| | | 0.0677 | 7.0 | 6013 | 1.9043 | 0.6736 | 0.4415 | 0.6756 |
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| | | 0.0404 | 8.0 | 6872 | 1.9555 | 0.6763 | 0.4521 | 0.6773 |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.40.2
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| | - Pytorch 2.8.0+cu128
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| | - Datasets 2.19.0
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| | - Tokenizers 0.19.1
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| | |
