DLthon_BERT_4
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: 0.0491
- F1: 0.9939
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: 0.0001
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 140 | 0.1991 | 0.9457 |
No log | 2.0 | 280 | 0.0872 | 0.9798 |
No log | 3.0 | 420 | 0.0520 | 0.9899 |
0.2431 | 4.0 | 560 | 0.0496 | 0.9939 |
0.2431 | 5.0 | 700 | 0.0491 | 0.9939 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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Model tree for jhkim12/DLthon_BERT_4
Base model
beomi/kcbert-base