| | ---
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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-intent-class-weighted
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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
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
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| | # roberta-intent-class-weighted
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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: 1.5616
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| | - Accuracy: 0.6871
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| | - Macro F1: 0.4540
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| | - Weighted F1: 0.6864
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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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| | - lr_scheduler_warmup_ratio: 0.06
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| | - num_epochs: 5
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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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| | | 1.8729 | 1.0 | 859 | 1.5736 | 0.6703 | 0.3479 | 0.6513 |
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| | | 0.9142 | 2.0 | 1718 | 1.4981 | 0.6742 | 0.3999 | 0.6641 |
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| | | 0.639 | 3.0 | 2577 | 1.4641 | 0.6863 | 0.4465 | 0.6852 |
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| | | 0.4608 | 4.0 | 3436 | 1.5182 | 0.6853 | 0.4604 | 0.6834 |
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| | | 0.3498 | 5.0 | 4295 | 1.5616 | 0.6871 | 0.4540 | 0.6864 |
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| |
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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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| | |
