pretrained-bert-uncased-90

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

• Train Loss: 5.5801
• Validation Loss: 13.6573
• Epoch: 89

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
8.8978	9.5686	0
7.0524	9.6480	1
6.8578	10.5054	2
6.1054	10.4137	3
6.1268	10.4515	4
5.8614	10.4313	5
5.9680	10.7224	6
5.7868	11.2948	7
5.5465	10.7112	8
5.7115	10.8543	9
5.7908	11.6466	10
5.5664	11.5085	11
5.5865	11.4894	12
5.6421	11.2182	13
5.6626	11.4446	14
5.4587	11.2814	15
5.5299	11.6601	16
5.5408	12.0485	17
5.5092	11.9469	18
5.6606	12.4353	19
5.7420	12.7461	20
5.6078	12.1650	21
5.6612	12.2811	22
5.7503	12.4086	23
5.5609	12.6149	24
5.4806	12.4447	25
5.6898	12.8078	26
5.6168	12.4649	27
5.6292	12.5851	28
5.8481	12.5146	29
5.6491	12.6358	30
5.5755	12.6996	31
5.8218	12.7957	32
5.5641	13.1650	33
5.6044	12.5065	34
5.6762	12.3722	35
5.5931	12.7162	36
5.5727	12.6179	37
5.5761	12.9479	38
5.6360	13.0610	39
5.4503	13.0441	40
5.5689	13.1673	41
5.6327	13.2184	42
5.5567	12.8114	43
5.6322	13.1793	44
5.4677	13.1324	45
5.5865	13.2891	46
5.5352	13.5036	47
5.4867	13.5010	48
5.6926	13.1743	49
5.7545	13.1689	50
5.5422	13.3362	51
5.6094	13.3983	52
5.5993	13.3638	53
5.6803	13.3884	54
5.6102	12.7277	55
5.7204	13.1669	56
5.5271	13.5684	57
5.5265	13.5086	58
5.5679	13.8641	59
5.6738	13.1735	60
5.5423	13.3285	61
5.5020	13.6262	62
5.5065	13.4765	63
5.5919	13.5598	64
5.5684	13.1651	65
5.6378	13.4781	66
5.6661	13.0726	67
5.7996	13.6267	68
5.7453	13.4608	69
5.5720	13.3663	70
5.4926	13.6905	71
5.7386	13.5941	72
5.6016	13.3110	73
5.5905	14.0529	74
5.7030	13.7322	75
5.6801	13.4712	76
5.6202	13.7954	77
5.6230	13.8177	78
5.6288	13.4887	79
5.6207	13.5817	80
5.5904	13.7643	81
5.6685	14.1648	82
5.5031	14.1816	83
5.6752	13.9170	84
5.6140	13.6953	85
5.6929	13.4916	86
5.4762	13.8740	87
5.6537	13.9725	88
5.5801	13.6573	89

Framework versions

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