kcbert-large-finetuned-nsmc
This model is a fine-tuned version of beomi/kcbert-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2576
- Accuracy: 0.9137
- F1: 0.9137
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.267 | 1.0 | 3750 | 0.2231 | 0.9106 | 0.9106 |
| 0.1427 | 2.0 | 7500 | 0.2576 | 0.9137 | 0.9137 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for metamath/kcbert-large-finetuned-nsmc
Base model
beomi/kcbert-large