---
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: 0.1418
- Validation Loss: 0.3009
- Epoch: 29

## 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 |
|:----------:|:---------------:|:-----:|
| 4.4155     | 1.9300          | 0     |
| 1.4995     | 1.0293          | 1     |
| 1.0445     | 0.8365          | 2     |
| 0.8775     | 0.7569          | 3     |
| 0.8198     | 0.7778          | 4     |
| 0.7619     | 0.7430          | 5     |
| 0.7324     | 0.7259          | 6     |
| 0.7234     | 0.7214          | 7     |
| 0.6697     | 0.6819          | 8     |
| 0.6599     | 0.6673          | 9     |
| 0.6387     | 0.6433          | 10    |
| 0.6227     | 0.6651          | 11    |
| 0.6017     | 0.6128          | 12    |
| 0.5820     | 0.6430          | 13    |
| 0.5229     | 0.5611          | 14    |
| 0.4617     | 0.4675          | 15    |
| 0.4071     | 0.4463          | 16    |
| 0.3495     | 0.4213          | 17    |
| 0.3202     | 0.4103          | 18    |
| 0.2875     | 0.4477          | 19    |
| 0.2528     | 0.3244          | 20    |
| 0.2331     | 0.4037          | 21    |
| 0.2117     | 0.3041          | 22    |
| 0.1943     | 0.3069          | 23    |
| 0.1805     | 0.3385          | 24    |
| 0.2267     | 0.3347          | 25    |
| 0.2049     | 0.2993          | 26    |
| 0.1800     | 0.3792          | 27    |
| 0.1583     | 0.2905          | 28    |
| 0.1418     | 0.3009          | 29    |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1