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kcbert-large-finetuned-unsmile
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: 0.1240
- Lrap: 0.8816
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 256
- 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 | Lrap |
|---|---|---|---|---|
| No log | 0.99 | 58 | 0.2090 | 0.8098 |
| No log | 1.99 | 116 | 0.1386 | 0.8707 |
| No log | 2.99 | 174 | 0.1263 | 0.8795 |
| No log | 3.99 | 232 | 0.1232 | 0.8823 |
| No log | 4.99 | 290 | 0.1240 | 0.8816 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.17.0
- Tokenizers 0.12.1
