NMTIndoBaliBART / README.md
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metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
  - generated_from_keras_callback
model-index:
  - name: pijarcandra22/NMTIndoBaliBART
    results: []

pijarcandra22/NMTIndoBaliBART

This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 5.5380
  • Validation Loss: 5.5728
  • Epoch: 135

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
9.7885 5.6003 0
5.5737 5.5523 1
5.5346 5.5361 2
5.5189 5.5283 3
5.5149 5.5252 4
5.5123 5.5233 5
5.5116 5.5485 6
5.5095 5.5314 7
5.5120 5.5569 8
5.5137 5.5239 9
5.5170 5.5289 10
5.5180 5.5298 11
5.5217 5.5513 12
5.5219 5.5344 13
5.5248 5.5366 14
5.5268 5.5493 15
5.5260 5.5313 16
5.5290 5.5462 17
5.5299 5.5570 18
5.5293 5.5480 19
5.5378 5.5524 20
5.5317 5.5740 21
5.5328 5.5543 22
5.5327 5.5537 23
5.5330 5.5356 24
5.5304 5.5492 25
5.5355 5.5388 26
5.5337 5.5812 27
5.5355 5.5598 28
5.5348 5.5489 29
5.5373 5.5526 30
5.5357 5.5575 31
5.5377 5.5439 32
5.5404 5.5367 33
5.5383 5.5819 34
5.5359 5.5815 35
5.5370 5.5499 36
5.5340 5.5622 37
5.5373 5.5667 38
5.5360 5.5548 39
5.5327 5.5555 40
5.5365 5.5642 41
5.5375 5.5496 42
5.5336 5.5424 43
5.5359 5.5761 44
5.5360 5.5821 45
5.5362 5.5742 46
5.5352 5.5635 47
5.5335 5.5507 48
5.5340 5.5613 49
5.5368 5.5599 50
5.5375 5.5541 51
5.5368 5.5536 52
5.5366 5.5438 53
5.5363 5.5497 54
5.5364 5.5721 55
5.5388 5.5493 56
5.5361 5.5719 57
5.5372 5.5920 58
5.5346 5.5534 59
5.5354 5.5526 60
5.5357 5.5788 61
5.5370 5.5531 62
5.5374 5.5613 63
5.5366 5.5585 64
5.5370 5.5652 65
5.5354 5.5463 66
5.5354 5.5689 67
5.5355 5.5508 68
5.5350 5.5522 69
5.5334 5.5574 70
5.5354 5.5555 71
5.5354 5.5503 72
5.5368 5.5562 73
5.5373 5.5524 74
5.5356 5.5544 75
5.5365 5.5508 76
5.5357 5.5650 77
5.5355 5.5665 78
5.5365 5.5471 79
5.5356 5.5535 80
5.5357 5.5801 81
5.5354 5.5570 82
5.5361 5.5596 83
5.5377 5.5584 84
5.5333 5.5570 85
5.5348 5.5513 86
5.5367 5.5508 87
5.5354 5.5333 88
5.5375 5.5530 89
5.5353 5.5386 90
5.5372 5.5966 91
5.5365 5.5582 92
5.5349 5.5776 93
5.5348 5.5700 94
5.5356 5.5518 95
5.5371 5.5692 96
5.5374 5.5572 97
5.5369 5.5621 98
5.5343 5.5593 99
5.5372 5.5698 100
5.5367 5.5422 101
5.5366 5.5846 102
5.5387 5.5687 103
5.5377 5.5590 104
5.5307 5.5640 105
5.5360 5.5421 106
5.5355 5.5542 107
5.5346 5.5460 108
5.5375 5.5610 109
5.5332 5.5676 110
5.5355 5.5364 111
5.5332 5.5630 112
5.5363 5.5600 113
5.5362 5.5705 114
5.5358 5.5700 115
5.5368 5.5578 116
5.5364 5.5531 117
5.5345 5.5688 118
5.5350 5.5620 119
5.5336 5.5764 120
5.5364 5.5476 121
5.5358 5.5623 122
5.5364 5.5569 123
5.5337 5.5713 124
5.5346 5.5936 125
5.5357 5.5645 126
5.5358 5.5566 127
5.5399 5.5494 128
5.5362 5.5586 129
5.5394 5.5611 130
5.5355 5.5691 131
5.5361 5.5471 132
5.5343 5.5549 133
5.5379 5.5587 134
5.5380 5.5728 135

Framework versions

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