|
--- |
|
license: mit |
|
base_model: gogamza/kobart-base-v2 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: qa_kor_math |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# qa_kor_math |
|
|
|
This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co./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 |
|
|
