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youtube_comment_sentiment_kcbert_finetune
Mingjj/youtube_comment_sentiment_kcbert_finetune
youtube_comment_sentiment_kcbert_finetune is a text classification model from Mingjj. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 12, 2025
- Updated
- Dec 12, 2025
- SHA
- af5d8481
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
youtube_comment_sentiment_kcbert_finetune
This model is a fine-tuned version of beomi/kcbert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7068
- Accuracy: {'accuracy': 0.7691387559808612}
- F1 Score: {'f1': 0.7624618153347268}
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| No log | 1.0 | 74 | 0.7068 | {'accuracy': 0.7691387559808612} | {'f1': 0.7624618153347268} |
| No log | 2.0 | 148 | 0.7671 | {'accuracy': 0.7787081339712919} | {'f1': 0.7808704180958316} |
| No log | 3.0 | 222 | 0.8857 | {'accuracy': 0.7942583732057417} | {'f1': 0.7945911253986201} |
| No log | 4.0 | 296 | 0.9936 | {'accuracy': 0.8038277511961722} | {'f1': 0.8042637284132086} |
| No log | 5.0 | 370 | 1.0303 | {'accuracy': 0.7990430622009569} | {'f1': 0.7997293347405633} |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 12, 2025
- Updated
- Dec 12, 2025