---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_keras_callback
model-index:
- name: pijarcandra22/BartIndo2Bali
  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. -->

# pijarcandra22/BartIndo2Bali

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1151
- Validation Loss: 2.6202
- Epoch: 99

## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.3767     | 3.6194          | 0     |
| 3.5364     | 3.1996          | 1     |
| 3.1525     | 2.9458          | 2     |
| 2.8777     | 2.8118          | 3     |
| 2.6993     | 2.6979          | 4     |
| 2.5550     | 2.6071          | 5     |
| 2.4536     | 2.5362          | 6     |
| 2.3338     | 2.4572          | 7     |
| 2.2394     | 2.3878          | 8     |
| 2.1466     | 2.3692          | 9     |
| 2.0795     | 2.3189          | 10    |
| 2.0061     | 2.2674          | 11    |
| 1.9321     | 2.2393          | 12    |
| 1.8837     | 2.2181          | 13    |
| 1.8224     | 2.2002          | 14    |
| 1.7626     | 2.1671          | 15    |
| 1.7251     | 2.1386          | 16    |
| 1.6624     | 2.1245          | 17    |
| 1.6191     | 2.1134          | 18    |
| 1.6177     | 2.1061          | 19    |
| 1.5524     | 2.0845          | 20    |
| 1.4965     | 2.0750          | 21    |
| 1.4618     | 2.0527          | 22    |
| 1.4188     | 2.0584          | 23    |
| 1.3774     | 2.0359          | 24    |
| 1.3469     | 2.0567          | 25    |
| 1.3113     | 2.0295          | 26    |
| 1.2791     | 2.0134          | 27    |
| 1.2436     | 2.0431          | 28    |
| 1.1915     | 2.0201          | 29    |
| 1.1815     | 2.0283          | 30    |
| 1.1314     | 2.0230          | 31    |
| 1.1071     | 2.0424          | 32    |
| 1.0781     | 2.0357          | 33    |
| 1.0429     | 2.0208          | 34    |
| 1.0134     | 2.0458          | 35    |
| 0.9799     | 2.0466          | 36    |
| 0.9567     | 2.0592          | 37    |
| 0.9261     | 2.0278          | 38    |
| 0.8931     | 2.0641          | 39    |
| 0.8742     | 2.0783          | 40    |
| 0.8397     | 2.0781          | 41    |
| 0.8228     | 2.1010          | 42    |
| 0.7819     | 2.1042          | 43    |
| 0.7667     | 2.1302          | 44    |
| 0.7508     | 2.1193          | 45    |
| 0.7136     | 2.1372          | 46    |
| 0.6849     | 2.1513          | 47    |
| 0.6625     | 2.1747          | 48    |
| 0.6451     | 2.1936          | 49    |
| 0.6114     | 2.1650          | 50    |
| 0.5907     | 2.2176          | 51    |
| 0.5781     | 2.2313          | 52    |
| 0.5594     | 2.2287          | 53    |
| 0.5361     | 2.2260          | 54    |
| 0.5168     | 2.2444          | 55    |
| 0.5022     | 2.2660          | 56    |
| 0.4826     | 2.2912          | 57    |
| 0.4607     | 2.2922          | 58    |
| 0.4442     | 2.2912          | 59    |
| 0.4262     | 2.3032          | 60    |
| 0.4050     | 2.3335          | 61    |
| 0.4005     | 2.3327          | 62    |
| 0.3826     | 2.3379          | 63    |
| 0.3658     | 2.3369          | 64    |
| 0.3442     | 2.3629          | 65    |
| 0.3384     | 2.3887          | 66    |
| 0.3287     | 2.3868          | 67    |
| 0.3140     | 2.3609          | 68    |
| 0.3078     | 2.4009          | 69    |
| 0.2953     | 2.4071          | 70    |
| 0.2855     | 2.4421          | 71    |
| 0.2715     | 2.4290          | 72    |
| 0.2647     | 2.4227          | 73    |
| 0.2483     | 2.4457          | 74    |
| 0.2402     | 2.4582          | 75    |
| 0.2355     | 2.4509          | 76    |
| 0.2272     | 2.4788          | 77    |
| 0.2198     | 2.4795          | 78    |
| 0.2077     | 2.4786          | 79    |
| 0.1989     | 2.5080          | 80    |
| 0.1992     | 2.4929          | 81    |
| 0.1905     | 2.5120          | 82    |
| 0.1880     | 2.5345          | 83    |
| 0.1773     | 2.5147          | 84    |
| 0.1734     | 2.5270          | 85    |
| 0.1663     | 2.5399          | 86    |
| 0.1618     | 2.5581          | 87    |
| 0.1576     | 2.5533          | 88    |
| 0.1550     | 2.5177          | 89    |
| 0.1475     | 2.5689          | 90    |
| 0.1453     | 2.5720          | 91    |
| 0.1398     | 2.5526          | 92    |
| 0.1357     | 2.5638          | 93    |
| 0.1325     | 2.5782          | 94    |
| 0.1293     | 2.6026          | 95    |
| 0.1263     | 2.6147          | 96    |
| 0.1257     | 2.6056          | 97    |
| 0.1149     | 2.6323          | 98    |
| 0.1151     | 2.6202          | 99    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0