distilbert-base-turkish-cased-allnli_tr

emrecan/distilbert-base-turkish-cased-allnli_tr

distilbert-base-turkish-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: distilbert
Access: Public
Created: Mar 2, 2022
Updated: Jun 8, 2024
SHA: 9b31343f

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Base models

dbmdz/distilbert-base-turkish-cased

Datasets

nli_tr

Spaces

Model card

From the Hugging Face model README

distilbert-base-turkish-cased_allnli_tr

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

Loss: 0.6481
Accuracy: 0.7381

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
0.94	0.03	1000	0.9074	0.5813
0.8102	0.07	2000	0.8802	0.5949
0.7737	0.1	3000	0.8491	0.6155
0.7576	0.14	4000	0.8283	0.6261
0.7286	0.17	5000	0.8150	0.6362
0.7162	0.2	6000	0.7998	0.6400
0.7092	0.24	7000	0.7830	0.6565
0.6962	0.27	8000	0.7653	0.6629
0.6876	0.31	9000	0.7630	0.6687
0.6778	0.34	10000	0.7475	0.6739
0.6737	0.37	11000	0.7495	0.6781
0.6712	0.41	12000	0.7350	0.6826
0.6559	0.44	13000	0.7274	0.6897
0.6493	0.48	14000	0.7248	0.6902
0.6483	0.51	15000	0.7263	0.6858
0.6445	0.54	16000	0.7070	0.6978
0.6467	0.58	17000	0.7083	0.6981
0.6332	0.61	18000	0.6996	0.7004
0.6288	0.65	19000	0.6979	0.6978
0.6308	0.68	20000	0.6912	0.7040
0.622	0.71	21000	0.6904	0.7092
0.615	0.75	22000	0.6872	0.7094
0.6186	0.78	23000	0.6877	0.7075
0.6183	0.82	24000	0.6818	0.7111
0.6115	0.85	25000	0.6856	0.7122
0.608	0.88	26000	0.6697	0.7179
0.6071	0.92	27000	0.6727	0.7181
0.601	0.95	28000	0.6798	0.7118
0.6018	0.99	29000	0.6854	0.7071
0.5762	1.02	30000	0.6697	0.7214
0.5507	1.05	31000	0.6710	0.7185
0.5575	1.09	32000	0.6709	0.7226
0.5493	1.12	33000	0.6659	0.7191
0.5464	1.15	34000	0.6709	0.7232
0.5595	1.19	35000	0.6642	0.7220
0.5446	1.22	36000	0.6709	0.7202
0.5524	1.26	37000	0.6751	0.7148
0.5473	1.29	38000	0.6642	0.7209
0.5477	1.32	39000	0.6662	0.7223
0.5522	1.36	40000	0.6586	0.7227
0.5406	1.39	41000	0.6602	0.7258
0.54	1.43	42000	0.6564	0.7273
0.5458	1.46	43000	0.6780	0.7213
0.5448	1.49	44000	0.6561	0.7235
0.5418	1.53	45000	0.6600	0.7253
0.5408	1.56	46000	0.6616	0.7274
0.5451	1.6	47000	0.6557	0.7283
0.5385	1.63	48000	0.6583	0.7295
0.5261	1.66	49000	0.6468	0.7325
0.5364	1.7	50000	0.6447	0.7329
0.5294	1.73	51000	0.6429	0.7320
0.5332	1.77	52000	0.6508	0.7272
0.5274	1.8	53000	0.6492	0.7326
0.5286	1.83	54000	0.6470	0.7318
0.5359	1.87	55000	0.6393	0.7354
0.5366	1.9	56000	0.6445	0.7367
0.5296	1.94	57000	0.6413	0.7313
0.5346	1.97	58000	0.6393	0.7315
0.5264	2.0	59000	0.6448	0.7357
0.4857	2.04	60000	0.6640	0.7335
0.4888	2.07	61000	0.6612	0.7318
0.4964	2.11	62000	0.6516	0.7337
0.493	2.14	63000	0.6503	0.7356
0.4961	2.17	64000	0.6519	0.7348
0.4847	2.21	65000	0.6517	0.7327
0.483	2.24	66000	0.6555	0.7310
0.4857	2.28	67000	0.6525	0.7312
0.484	2.31	68000	0.6444	0.7342
0.4792	2.34	69000	0.6508	0.7330
0.488	2.38	70000	0.6513	0.7344
0.472	2.41	71000	0.6547	0.7346
0.4872	2.45	72000	0.6500	0.7342
0.4782	2.48	73000	0.6585	0.7358
0.481	2.51	74000	0.6477	0.7356
0.4822	2.55	75000	0.6587	0.7346
0.4728	2.58	76000	0.6572	0.7340
0.4841	2.62	77000	0.6443	0.7374
0.4885	2.65	78000	0.6494	0.7362
0.4752	2.68	79000	0.6509	0.7382
0.4883	2.72	80000	0.6457	0.7371
0.4888	2.75	81000	0.6497	0.7364
0.4844	2.79	82000	0.6481	0.7376
0.4833	2.82	83000	0.6451	0.7389
0.48	2.85	84000	0.6423	0.7373
0.4832	2.89	85000	0.6477	0.7357
0.4805	2.92	86000	0.6464	0.7379
0.4775	2.96	87000	0.6477	0.7380
0.4843	2.99	88000	0.6481	0.7381

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: distilbert
License: apache-2.0
Languages: tr
Created: Mar 2, 2022
Updated: Jun 8, 2024