pijarcandra22/t5Bali2Indo

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.4589
• Validation Loss: 1.5981
• Epoch: 97

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
0.5701	1.5227	0
0.5700	1.5142	1
0.5690	1.5212	2
0.5623	1.5221	3
0.5686	1.5265	4
0.5592	1.5261	5
0.5619	1.5208	6
0.5615	1.5224	7
0.5679	1.5230	8
0.5630	1.5250	9
0.5621	1.5238	10
0.5617	1.5270	11
0.5520	1.5271	12
0.5530	1.5347	13
0.5578	1.5278	14
0.5497	1.5280	15
0.5513	1.5333	16
0.5506	1.5371	17
0.5504	1.5337	18
0.5499	1.5374	19
0.5436	1.5405	20
0.5420	1.5382	21
0.5462	1.5377	22
0.5402	1.5367	23
0.5422	1.5345	24
0.5408	1.5385	25
0.5434	1.5378	26
0.5343	1.5381	27
0.5368	1.5404	28
0.5410	1.5407	29
0.5368	1.5417	30
0.5344	1.5431	31
0.5343	1.5428	32
0.5343	1.5454	33
0.5300	1.5499	34
0.5325	1.5505	35
0.5269	1.5427	36
0.5217	1.5493	37
0.5197	1.5560	38
0.5247	1.5520	39
0.5200	1.5557	40
0.5270	1.5551	41
0.5241	1.5518	42
0.5163	1.5492	43
0.5227	1.5520	44
0.5221	1.5552	45
0.5123	1.5523	46
0.5173	1.5572	47
0.5194	1.5571	48
0.5159	1.5566	49
0.5137	1.5591	50
0.5127	1.5533	51
0.5094	1.5516	52
0.5095	1.5574	53
0.5023	1.5609	54
0.5040	1.5604	55
0.5019	1.5650	56
0.5093	1.5577	57
0.5050	1.5592	58
0.5069	1.5623	59
0.4998	1.5635	60
0.4936	1.5674	61
0.4997	1.5651	62
0.4970	1.5648	63
0.4927	1.5651	64
0.4933	1.5719	65
0.4951	1.5699	66
0.4963	1.5690	67
0.4906	1.5728	68
0.4927	1.5740	69
0.4884	1.5763	70
0.4917	1.5766	71
0.4854	1.5740	72
0.4793	1.5741	73
0.4824	1.5790	74
0.4830	1.5760	75
0.4842	1.5784	76
0.4786	1.5794	77
0.4815	1.5733	78
0.4791	1.5800	79
0.4784	1.5796	80
0.4743	1.5835	81
0.4766	1.5832	82
0.4767	1.5814	83
0.4800	1.5832	84
0.4787	1.5847	85
0.4681	1.5849	86
0.4727	1.5875	87
0.4716	1.5838	88
0.4686	1.5849	89
0.4708	1.5851	90
0.4697	1.5911	91
0.4705	1.5910	92
0.4695	1.5934	93
0.4670	1.5914	94
0.4643	1.5969	95
0.4636	1.5945	96
0.4589	1.5981	97

Framework versions

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