bedus-creation/eng-limbu-t5-manual-002

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: 3.0687
• Validation Loss: 3.7774
• 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
6.7285	5.8526	0
5.8608	5.3145	1
5.3625	5.0804	2
5.1012	4.9629	3
4.9323	4.8258	4
4.7733	4.7266	5
4.6924	4.6181	6
4.5603	4.5446	7
4.4889	4.4844	8
4.4311	4.4172	9
4.3759	4.3850	10
4.3222	4.3224	11
4.2802	4.2932	12
4.2507	4.2517	13
4.1858	4.2192	14
4.1643	4.2057	15
4.1406	4.2012	16
4.0881	4.1809	17
4.0782	4.1407	18
4.0536	4.1458	19
4.0260	4.1167	20
4.0093	4.1147	21
3.9739	4.0881	22
3.9548	4.0896	23
3.9533	4.0832	24
3.9363	4.0328	25
3.9258	4.0340	26
3.8973	4.0176	27
3.8789	4.0131	28
3.8784	4.0032	29
3.8391	3.9896	30
3.8506	3.9902	31
3.8081	3.9742	32
3.8068	3.9699	33
3.7911	3.9409	34
3.7909	3.9411	35
3.7658	3.9416	36
3.7317	3.9270	37
3.7404	3.9225	38
3.7321	3.9159	39
3.7112	3.9071	40
3.7039	3.9003	41
3.6980	3.8723	42
3.6639	3.8921	43
3.6612	3.8674	44
3.6497	3.8624	45
3.6284	3.8694	46
3.6403	3.8701	47
3.5968	3.8516	48
3.5749	3.8435	49
3.5751	3.8545	50
3.5736	3.8304	51
3.5722	3.8247	52
3.5431	3.8396	53
3.5280	3.8265	54
3.5288	3.8225	55
3.5014	3.8248	56
3.5046	3.7864	57
3.5144	3.8151	58
3.4876	3.8117	59
3.4744	3.8099	60
3.4667	3.8110	61
3.4503	3.8165	62
3.4516	3.7818	63
3.4484	3.8165	64
3.4146	3.8282	65
3.3911	3.8151	66
3.4345	3.7842	67
3.4155	3.7777	68
3.3755	3.8011	69
3.3595	3.7737	70
3.3727	3.7744	71
3.3670	3.7683	72
3.3493	3.7721	73
3.3337	3.7927	74
3.3260	3.7670	75
3.3160	3.7802	76
3.3120	3.7885	77
3.3101	3.7675	78
3.2842	3.7837	79
3.2765	3.7607	80
3.2684	3.7805	81
3.2576	3.7578	82
3.2637	3.7661	83
3.2414	3.7964	84
3.2241	3.7806	85
3.2294	3.7762	86
3.2067	3.7526	87
3.1882	3.7809	88
3.2020	3.7670	89
3.1646	3.7671	90
3.1873	3.7586	91
3.1619	3.7843	92
3.1608	3.7573	93
3.1648	3.7654	94
3.1107	3.7811	95
3.1221	3.7974	96
3.0947	3.7810	97
3.1046	3.7647	98
3.0687	3.7774	99

Framework versions

• Transformers 4.33.2
• TensorFlow 2.13.0
• Datasets 2.14.5
• Tokenizers 0.13.3