pretrained-bert-uncased-100

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

• Train Loss: nan
• Validation Loss: nan
• 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': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
8.9143	9.5645	0
7.0594	9.6348	1
6.5846	10.4810	2
6.1703	10.3871	3
6.2204	10.4579	4
5.9912	11.0864	5
6.1670	10.8475	6
5.9434	11.3010	7
5.7437	10.9369	8
5.8586	11.1204	9
5.8595	11.5750	10
5.7608	12.0360	11
5.7219	11.4627	12
5.8005	11.6418	13
5.8040	11.7480	14
5.6217	11.9184	15
5.7095	11.9534	16
5.7426	12.3718	17
5.6365	11.7388	18
5.6291	12.1911	19
5.7437	12.3435	20
5.6589	12.1656	21
5.6835	12.1785	22
5.7466	12.1934	23
5.5470	12.4191	24
5.4824	12.3100	25
5.7151	12.7568	26
5.6431	12.3509	27
5.6188	12.4724	28
5.8535	12.3254	29
5.6457	12.5312	30
5.5622	12.6608	31
5.8279	12.6227	32
5.5720	13.0677	33
5.6025	12.5078	34
5.6830	12.2650	35
5.6089	12.5420	36
5.5842	12.4246	37
5.5823	12.8527	38
5.6300	12.9306	39
5.4753	13.0506	40
5.5736	12.8653	41
5.6237	13.1275	42
5.5517	12.6621	43
5.6275	13.0830	44
5.4596	13.0334	45
5.5789	13.1859	46
5.5381	13.4193	47
5.4859	13.3659	48
5.6895	13.1080	49
5.7514	13.1102	50
5.5406	13.3108	51
5.6091	13.3639	52
5.5978	13.3497	53
5.6819	13.3768	54
5.6097	12.7091	55
5.7161	13.1289	56
5.5263	13.5468	57
5.5250	13.4408	58
5.5677	13.7557	59
5.6698	13.0456	60
5.5404	13.2635	61
5.5019	13.5839	62
5.5027	13.3752	63
5.5898	13.5648	64
5.5646	13.1321	65
5.6336	13.4493	66
5.6596	13.0167	67
5.7952	13.6155	68
5.7404	13.4588	69
5.5704	13.3443	70
5.4927	13.6466	71
5.7395	13.6197	72
5.5994	13.3629	73
5.5902	14.0645	74
5.7020	13.7721	75
5.6767	13.4775	76
5.6172	13.7838	77
5.6232	13.7676	78
5.6285	13.4416	79
5.6174	13.5767	80
5.5878	13.7731	81
5.6670	14.1654	82
5.5013	14.2273	83
5.6745	13.9600	84
5.6135	13.8017	85
5.6932	13.6257	86
5.4745	13.9570	87
5.6542	14.0449	88
5.5748	13.6820	89
5.6025	13.7910	90
5.6333	14.4047	91
nan	nan	92
nan	nan	93
nan	nan	94
nan	nan	95
nan	nan	96
nan	nan	97
nan	nan	98
nan	nan	99

Framework versions

• Transformers 4.27.0.dev0
• TensorFlow 2.9.2
• Datasets 2.9.0
• Tokenizers 0.13.2