metadata
license: mit
base_model: gogamza/kobart-base-v2
tags:
- generated_from_trainer
model-index:
- name: qa_kor_math
results: []
qa_kor_math
This model is a fine-tuned version of gogamza/kobart-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2586
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.63 | 100 | 2.9907 |
| No log | 1.26 | 200 | 0.9196 |
| No log | 1.89 | 300 | 0.5858 |
| No log | 2.52 | 400 | 0.4351 |
| 2.4889 | 3.14 | 500 | 0.3693 |
| 2.4889 | 3.77 | 600 | 0.3356 |
| 2.4889 | 4.4 | 700 | 0.3182 |
| 2.4889 | 5.03 | 800 | 0.3017 |
| 2.4889 | 5.66 | 900 | 0.2949 |
| 0.3483 | 6.29 | 1000 | 0.2798 |
| 0.3483 | 6.92 | 1100 | 0.2748 |
| 0.3483 | 7.55 | 1200 | 0.2695 |
| 0.3483 | 8.18 | 1300 | 0.2649 |
| 0.3483 | 8.81 | 1400 | 0.2610 |
| 0.2753 | 9.43 | 1500 | 0.2586 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2