convbert-base-turkish-mc4-cased-allnli_tr

emrecan/convbert-base-turkish-mc4-cased-allnli_tr

convbert-base-turkish-mc4-cased-allnli_tr is a zero-shot classification model from emrecan. Use it when you need labels you did not train the model on. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Zero-Shot Classification
Library: transformers
License: apache-2.0
Model type: convbert
Access: Public
Created: Mar 2, 2022
Updated: Dec 2, 2021
SHA: 84be0ca7

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Datasets

nli_tr

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Model card

From the Hugging Face model README

convbert-base-turkish-mc4-cased_allnli_tr

This model is a fine-tuned version of dbmdz/convbert-base-turkish-mc4-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5541
Accuracy: 0.8111

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:

learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7338	0.03	1000	0.6722	0.7236
0.603	0.07	2000	0.6465	0.7399
0.5605	0.1	3000	0.5801	0.7728
0.55	0.14	4000	0.5994	0.7626
0.529	0.17	5000	0.5720	0.7697
0.5196	0.2	6000	0.5692	0.7769
0.5117	0.24	7000	0.5725	0.7785
0.5044	0.27	8000	0.5532	0.7787
0.5016	0.31	9000	0.5546	0.7812
0.5031	0.34	10000	0.5461	0.7870
0.4949	0.37	11000	0.5725	0.7826
0.4894	0.41	12000	0.5419	0.7933
0.4796	0.44	13000	0.5278	0.7914
0.4795	0.48	14000	0.5193	0.7953
0.4713	0.51	15000	0.5534	0.7771
0.4738	0.54	16000	0.5098	0.8039
0.481	0.58	17000	0.5244	0.7958
0.4634	0.61	18000	0.5215	0.7972
0.465	0.65	19000	0.5129	0.7985
0.4624	0.68	20000	0.5062	0.8047
0.4597	0.71	21000	0.5114	0.8029
0.4571	0.75	22000	0.5070	0.8073
0.4602	0.78	23000	0.5115	0.7993
0.4552	0.82	24000	0.5085	0.8052
0.4538	0.85	25000	0.5118	0.7974
0.4517	0.88	26000	0.5036	0.8044
0.4517	0.92	27000	0.4930	0.8062
0.4413	0.95	28000	0.5307	0.7964
0.4483	0.99	29000	0.5195	0.7938
0.4036	1.02	30000	0.5238	0.8029
0.3724	1.05	31000	0.5125	0.8082
0.3777	1.09	32000	0.5099	0.8075
0.3753	1.12	33000	0.5172	0.8053
0.367	1.15	34000	0.5188	0.8053
0.3819	1.19	35000	0.5218	0.8046
0.363	1.22	36000	0.5202	0.7993
0.3794	1.26	37000	0.5240	0.8048
0.3749	1.29	38000	0.5026	0.8054
0.367	1.32	39000	0.5198	0.8075
0.3759	1.36	40000	0.5298	0.7993
0.3701	1.39	41000	0.5072	0.8091
0.3742	1.43	42000	0.5071	0.8098
0.3706	1.46	43000	0.5317	0.8037
0.3716	1.49	44000	0.5034	0.8052
0.3717	1.53	45000	0.5258	0.8012
0.3714	1.56	46000	0.5195	0.8050
0.3781	1.6	47000	0.5004	0.8104
0.3725	1.63	48000	0.5124	0.8113
0.3624	1.66	49000	0.5040	0.8094
0.3657	1.7	50000	0.4979	0.8111
0.3669	1.73	51000	0.4968	0.8100
0.3636	1.77	52000	0.5075	0.8079
0.36	1.8	53000	0.4985	0.8110
0.3624	1.83	54000	0.5125	0.8070
0.366	1.87	55000	0.4918	0.8117
0.3655	1.9	56000	0.5051	0.8109
0.3609	1.94	57000	0.5083	0.8105
0.3672	1.97	58000	0.5129	0.8085
0.3545	2.0	59000	0.5467	0.8109
0.2938	2.04	60000	0.5635	0.8049
0.29	2.07	61000	0.5781	0.8041
0.2992	2.11	62000	0.5470	0.8077
0.2957	2.14	63000	0.5765	0.8073
0.292	2.17	64000	0.5472	0.8106
0.2893	2.21	65000	0.5590	0.8085
0.2883	2.24	66000	0.5535	0.8064
0.2923	2.28	67000	0.5508	0.8095
0.2868	2.31	68000	0.5679	0.8098
0.2892	2.34	69000	0.5660	0.8057
0.292	2.38	70000	0.5494	0.8088
0.286	2.41	71000	0.5653	0.8085
0.2939	2.45	72000	0.5673	0.8070
0.286	2.48	73000	0.5600	0.8092
0.2844	2.51	74000	0.5508	0.8095
0.2913	2.55	75000	0.5645	0.8088
0.2859	2.58	76000	0.5677	0.8095
0.2892	2.62	77000	0.5598	0.8113
0.2898	2.65	78000	0.5618	0.8096
0.2814	2.68	79000	0.5664	0.8103
0.2917	2.72	80000	0.5484	0.8122
0.2907	2.75	81000	0.5522	0.8116
0.2896	2.79	82000	0.5540	0.8093
0.2907	2.82	83000	0.5469	0.8104
0.2882	2.85	84000	0.5471	0.8122
0.2878	2.89	85000	0.5532	0.8108
0.2858	2.92	86000	0.5511	0.8115
0.288	2.96	87000	0.5491	0.8111
0.2834	2.99	88000	0.5541	0.8111

Framework versions

Transformers 4.12.3
Pytorch 1.10.0+cu102
Datasets 1.15.1
Tokenizers 0.10.3

Task: Zero-Shot Classification
Library: transformers
Type: convbert
License: apache-2.0
Languages: tr
Created: Mar 2, 2022
Updated: Dec 2, 2021