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kcbert_nsmc_tuning
gigauser/kcbert_nsmc_tuning
kcbert_nsmc_tuning is a text classification model from gigauser. 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
- Jul 7, 2024
- Updated
- Jul 8, 2024
- SHA
- 78805ec5
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Base models
Datasets
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. -->
kcbert_nsmc_tuning
This model is a fine-tuned version of beomi/kcbert-base on the nsmc dataset. It achieves the following results on the evaluation set:
- Loss: 0.4492
- Accuracy: 0.9013
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1689 | 1.0 | 2344 | 0.2717 | 0.9006 |
| 0.0951 | 2.0 | 4688 | 0.3458 | 0.8995 |
| 0.051 | 3.0 | 7032 | 0.4492 | 0.9013 |
Framework versions
- Transformers 4.42.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 7, 2024
- Updated
- Jul 8, 2024