BartIndo2Bali – AI Model by pijarcandra22 | AlphaNeural AI

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pijarcandra22/
BartIndo2Bali

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text2text-generation

generated_from_keras_callback

facebook/bart-base

endpoints_compatible

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pijarcandra22/BartIndo2Bali

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: 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