mBart-small-dataset-i-eng-lim – AI Model by bedus-creation | AlphaNeural AI

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bedus-creation/
mBart-small-dataset-i-eng-lim

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text2text-generation

generated_from_keras_callback

endpoints_compatible

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bedus-creation/t5-small-dataset-i-eng-lim

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

Train Loss: 3.0827
Validation Loss: 3.6942
Epoch: 98

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
6.7704	5.9134	0
5.9151	5.3799	1
5.4499	5.1064	2
5.1740	4.9542	3
4.9818	4.8383	4
4.8642	4.7334	5
4.7371	4.6535	6
4.6666	4.5845	7
4.5665	4.5088	8
4.5159	4.4424	9
4.4477	4.4099	10
4.3651	4.3525	11
4.3303	4.3177	12
4.2885	4.2668	13
4.2273	4.2247	14
4.2048	4.1953	15
4.1743	4.1945	16
4.1337	4.1519	17
4.1091	4.1306	18
4.0812	4.1167	19
4.0489	4.1000	20
4.0184	4.0721	21
4.0134	4.0486	22
3.9739	4.0406	23
3.9381	4.0355	24
3.9363	4.0174	25
3.9039	4.0123	26
3.8887	3.9893	27
3.8742	3.9748	28
3.8520	3.9935	29
3.8403	3.9554	30
3.8126	3.9550	31
3.7920	3.9503	32
3.7767	3.9482	33
3.7509	3.9106	34
3.7589	3.9050	35
3.7469	3.8956	36
3.7217	3.8912	37
3.7002	3.8869	38
3.6859	3.8909	39
3.6904	3.8719	40
3.6422	3.8643	41
3.6361	3.8637	42
3.6395	3.8547	43
3.6267	3.8349	44
3.6040	3.8333	45
3.5906	3.8254	46
3.6037	3.8258	47
3.5775	3.8237	48
3.5683	3.8197	49
3.5499	3.8086	50
3.5351	3.7988	51
3.5217	3.8263	52
3.5196	3.7971	53
3.4942	3.7985	54
3.4878	3.7955	55
3.4725	3.7823	56
3.4716	3.7667	57
3.4676	3.7688	58
3.4488	3.7423	59
3.4474	3.7587	60
3.4346	3.7488	61
3.4313	3.7616	62
3.4023	3.7542	63
3.3851	3.7517	64
3.4024	3.7343	65
3.3738	3.7339	66
3.3656	3.7446	67
3.3645	3.7267	68
3.3614	3.7265	69
3.3399	3.7409	70
3.3287	3.7133	71
3.3140	3.7288	72
3.2964	3.7047	73
3.2872	3.7173	74
3.2904	3.7150	75
3.2749	3.7100	76
3.2713	3.7086	77
3.2675	3.7073	78
3.2569	3.6901	79
3.2469	3.6959	80
3.2353	3.7033	81
3.2394	3.7201	82
3.2163	3.7068	83
3.2121	3.6795	84
3.1908	3.7045	85
3.1841	3.7177	86
3.1706	3.7030	87
3.1591	3.6963	88
3.1646	3.6930	89
3.1293	3.7010	90
3.1635	3.6928	91
3.1310	3.6846	92
3.1286	3.6802	93
3.1235	3.6716	94
3.1133	3.6609	95
3.1135	3.6744	96
3.0875	3.6750	97
3.0827	3.6942	98

Framework versions

Transformers 4.33.2
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3