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

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: 5.5217
- Validation Loss: 5.6917
- Epoch: 124

## 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': 0.02, '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 |
|:----------:|:---------------:|:-----:|
| 9.3368     | 5.6757          | 0     |
| 5.5627     | 5.5987          | 1     |
| 5.5311     | 5.5419          | 2     |
| 5.5152     | 5.5201          | 3     |
| 5.5005     | 5.6477          | 4     |
| 5.4704     | 5.5914          | 5     |
| 5.4610     | 6.0922          | 6     |
| 5.4584     | 5.7137          | 7     |
| 5.4528     | 5.8658          | 8     |
| 5.4820     | 5.5628          | 9     |
| 5.4874     | 5.5309          | 10    |
| 5.4917     | 5.7595          | 11    |
| 5.4898     | 5.7333          | 12    |
| 5.4833     | 5.6789          | 13    |
| 5.4767     | 5.9588          | 14    |
| 5.4883     | 5.9895          | 15    |
| 5.4694     | 6.0100          | 16    |
| 5.4663     | 6.0316          | 17    |
| 5.4602     | 5.9233          | 18    |
| 5.4576     | 6.0051          | 19    |
| 5.4559     | 5.9966          | 20    |
| 5.4651     | 6.0025          | 21    |
| 5.4660     | 6.0160          | 22    |
| 5.4626     | 5.8324          | 23    |
| 5.4647     | 5.8383          | 24    |
| 5.4695     | 6.0272          | 25    |
| 5.4614     | 6.0724          | 26    |
| 5.4623     | 5.9454          | 27    |
| 5.4678     | 6.0196          | 28    |
| 5.4860     | 5.5949          | 29    |
| 5.4851     | 5.8838          | 30    |
| 5.4666     | 5.8506          | 31    |
| 5.4715     | 6.0391          | 32    |
| 5.4630     | 6.0870          | 33    |
| 5.4646     | 6.2195          | 34    |
| 5.4574     | 5.9696          | 35    |
| 5.4564     | 5.8970          | 36    |
| 5.4570     | 5.9522          | 37    |
| 5.4559     | 6.1518          | 38    |
| 5.4584     | 6.1860          | 39    |
| 5.4732     | 6.1168          | 40    |
| 5.4625     | 6.1588          | 41    |
| 5.4601     | 5.9868          | 42    |
| 5.4645     | 5.9606          | 43    |
| 5.4664     | 6.1495          | 44    |
| 5.4698     | 6.0152          | 45    |
| 5.4666     | 6.2713          | 46    |
| 5.4557     | 6.2708          | 47    |
| 5.4557     | 6.0003          | 48    |
| 5.4693     | 5.9321          | 49    |
| 5.4928     | 5.8971          | 50    |
| 5.5032     | 6.0766          | 51    |
| 5.4749     | 5.8919          | 52    |
| 5.4689     | 5.9853          | 53    |
| 5.4665     | 5.9329          | 54    |
| 5.4574     | 5.9770          | 55    |
| 5.4686     | 6.1022          | 56    |
| 5.4727     | 5.8973          | 57    |
| 5.4692     | 5.9633          | 58    |
| 5.4608     | 6.0480          | 59    |
| 5.4613     | 5.9596          | 60    |
| 5.4607     | 6.1158          | 61    |
| 5.4531     | 6.0617          | 62    |
| 5.4610     | 6.0375          | 63    |
| 5.4631     | 6.1184          | 64    |
| 5.4627     | 6.0465          | 65    |
| 5.4685     | 6.0011          | 66    |
| 5.4642     | 6.0828          | 67    |
| 5.4577     | 6.0883          | 68    |
| 5.4615     | 5.9523          | 69    |
| 5.4673     | 5.7216          | 70    |
| 5.4724     | 6.0274          | 71    |
| 5.4601     | 6.0344          | 72    |
| 5.4640     | 5.9661          | 73    |
| 5.4590     | 6.0013          | 74    |
| 5.4622     | 6.0172          | 75    |
| 5.4666     | 5.8407          | 76    |
| 5.4669     | 6.0261          | 77    |
| 5.4859     | 5.9295          | 78    |
| 5.5042     | 6.1254          | 79    |
| 5.4845     | 5.8930          | 80    |
| 5.5001     | 5.8867          | 81    |
| 5.4923     | 5.9480          | 82    |
| 5.4909     | 6.0475          | 83    |
| 5.4780     | 5.9289          | 84    |
| 5.4867     | 5.8134          | 85    |
| 5.4877     | 6.0032          | 86    |
| 5.4806     | 6.0884          | 87    |
| 5.4784     | 6.0567          | 88    |
| 5.4830     | 5.9790          | 89    |
| 5.4894     | 5.8919          | 90    |
| 5.4890     | 5.9626          | 91    |
| 5.4774     | 6.0267          | 92    |
| 5.5033     | 6.1150          | 93    |
| 5.4765     | 5.9776          | 94    |
| 5.4657     | 6.1395          | 95    |
| 5.4720     | 5.9938          | 96    |
| 5.4748     | 5.9656          | 97    |
| 5.4701     | 6.0163          | 98    |
| 5.4718     | 6.1462          | 99    |
| 5.4672     | 6.0804          | 100   |
| 5.4775     | 6.1055          | 101   |
| 5.4775     | 6.0936          | 102   |
| 5.4673     | 5.9839          | 103   |
| 5.4691     | 5.8972          | 104   |
| 5.4694     | 5.8271          | 105   |
| 5.5106     | 5.5305          | 106   |
| 5.5135     | 5.8806          | 107   |
| 5.4786     | 6.1380          | 108   |
| 5.4770     | 5.9899          | 109   |
| 5.4709     | 6.1072          | 110   |
| 5.4701     | 5.9356          | 111   |
| 5.4636     | 5.8304          | 112   |
| 5.4670     | 6.0451          | 113   |
| 5.4598     | 6.0311          | 114   |
| 5.4731     | 5.9862          | 115   |
| 5.4798     | 5.9589          | 116   |
| 5.4674     | 5.9356          | 117   |
| 5.4634     | 6.0088          | 118   |
| 5.4709     | 5.9534          | 119   |
| 5.4891     | 5.9995          | 120   |
| 5.4737     | 5.8611          | 121   |
| 5.4725     | 6.0112          | 122   |
| 5.4835     | 5.6280          | 123   |
| 5.5217     | 5.6917          | 124   |


### Framework versions

- Transformers 4.40.2
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1