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---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: madatnlp/gamza-bart-for-kormath
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# madatnlp/gamza-bart-for-kormath
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:
- Train Loss: 0.0460
- Validation Loss: 0.3173
- Epoch: 52
## 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:
- optimizer: {'name': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.3868 | 1.8720 | 0 |
| 1.5091 | 1.0768 | 1 |
| 1.0238 | 0.8972 | 2 |
| 0.8960 | 0.8375 | 3 |
| 0.8087 | 0.7618 | 4 |
| 0.7656 | 0.7196 | 5 |
| 0.7433 | 0.7023 | 6 |
| 0.7309 | 0.6992 | 7 |
| 0.6773 | 0.7008 | 8 |
| 0.6659 | 0.6752 | 9 |
| 0.6607 | 0.7347 | 10 |
| 0.6370 | 0.6033 | 11 |
| 0.6037 | 0.6806 | 12 |
| 0.5957 | 0.6370 | 13 |
| 0.5740 | 0.6413 | 14 |
| 0.5005 | 0.5002 | 15 |
| 0.4385 | 0.4821 | 16 |
| 0.5042 | 0.4898 | 17 |
| 0.4445 | 0.5218 | 18 |
| 0.3990 | 0.4771 | 19 |
| 0.3497 | 0.4173 | 20 |
| 0.3294 | 0.4232 | 21 |
| 0.3019 | 0.3936 | 22 |
| 0.2868 | 0.4212 | 23 |
| 0.2565 | 0.3401 | 24 |
| 0.2404 | 0.3912 | 25 |
| 0.2235 | 0.3484 | 26 |
| 0.1976 | 0.3357 | 27 |
| 0.1998 | 0.3392 | 28 |
| 0.1788 | 0.3075 | 29 |
| 0.1705 | 0.3615 | 30 |
| 0.1642 | 0.3466 | 31 |
| 0.1510 | 0.3325 | 32 |
| 0.1402 | 0.3729 | 33 |
| 0.1342 | 0.3425 | 34 |
| 0.1276 | 0.3039 | 35 |
| 0.1093 | 0.3276 | 36 |
| 0.1048 | 0.3034 | 37 |
| 0.0951 | 0.3472 | 38 |
| 0.0971 | 0.3407 | 39 |
| 0.0849 | 0.3516 | 40 |
| 0.0868 | 0.2757 | 41 |
| 0.0868 | 0.2383 | 42 |
| 0.0766 | 0.3127 | 43 |
| 0.0734 | 0.3324 | 44 |
| 0.0694 | 0.3654 | 45 |
| 0.0626 | 0.2692 | 46 |
| 0.0584 | 0.2403 | 47 |
| 0.0565 | 0.3741 | 48 |
| 0.0567 | 0.2839 | 49 |
| 0.0523 | 0.2387 | 50 |
| 0.0525 | 0.2629 | 51 |
| 0.0460 | 0.3173 | 52 |
### Framework versions
- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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