distilbert_oscarth_0100 – AI Model by bigmorning | AlphaNeural AI

You can deploy this model and start earning money today!

bigmorning/
distilbert_oscarth_0100

like

0

generated_from_keras_callback

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert_oscarth_0100

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

Train Loss: 1.0777
Validation Loss: 1.0396
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
4.1327	2.9983	0
2.7813	2.4562	1
2.4194	2.2066	2
2.2231	2.0562	3
2.0894	1.9450	4
1.9905	1.8621	5
1.9148	1.7941	6
1.8508	1.7363	7
1.7976	1.6909	8
1.7509	1.6488	9
1.7126	1.6124	10
1.6764	1.5835	11
1.6450	1.5521	12
1.6175	1.5282	13
1.5919	1.5045	14
1.5679	1.4833	15
1.5476	1.4627	16
1.5271	1.4498	17
1.5098	1.4270	18
1.4909	1.4161	19
1.4760	1.3995	20
1.4609	1.3864	21
1.4475	1.3717	22
1.4333	1.3590	23
1.4203	1.3478	24
1.4093	1.3403	25
1.3980	1.3296	26
1.3875	1.3176	27
1.3773	1.3094	28
1.3674	1.3011	29
1.3579	1.2920	30
1.3497	1.2826	31
1.3400	1.2764	32
1.3326	1.2694	33
1.3236	1.2635	34
1.3169	1.2536	35
1.3096	1.2477	36
1.3024	1.2408	37
1.2957	1.2364	38
1.2890	1.2296	39
1.2818	1.2236	40
1.2751	1.2168	41
1.2691	1.2126	42
1.2644	1.2044	43
1.2583	1.2008	44
1.2529	1.1962	45
1.2473	1.1919	46
1.2416	1.1857	47
1.2365	1.1812	48
1.2318	1.1765	49
1.2273	1.1738	50
1.2224	1.1672	51
1.2177	1.1673	52
1.2132	1.1595	53
1.2084	1.1564	54
1.2033	1.1518	55
1.1993	1.1481	56
1.1966	1.1445	57
1.1924	1.1412	58
1.1876	1.1378	59
1.1834	1.1340	60
1.1806	1.1329	61
1.1783	1.1289	62
1.1739	1.1251	63
1.1705	1.1223	64
1.1669	1.1192	65
1.1628	1.1172	66
1.1599	1.1140	67
1.1570	1.1084	68
1.1526	1.1081	69
1.1496	1.1043	70
1.1463	1.0999	71
1.1438	1.1006	72
1.1397	1.0964	73
1.1378	1.0918	74
1.1347	1.0917	75
1.1319	1.0889	76
1.1296	1.0855	77
1.1271	1.0848	78
1.1236	1.0821	79
1.1212	1.0801	80
1.1185	1.0771	81
1.1155	1.0750	82
1.1139	1.0726	83
1.1110	1.0713	84
1.1082	1.0689	85
1.1057	1.0658	86
1.1031	1.0641	87
1.1018	1.0619	88
1.0985	1.0606	89
1.0976	1.0590	90
1.0944	1.0570	91
1.0926	1.0561	92
1.0905	1.0502	93
1.0877	1.0495	94
1.0869	1.0508	95
1.0844	1.0465	96
1.0824	1.0450	97
1.0798	1.0448	98
1.0777	1.0396	99

Framework versions

Transformers 4.20.1
TensorFlow 2.8.2
Datasets 2.3.2
Tokenizers 0.12.1