wav2vec2-xls-r-1b-turkish

Baybars/wav2vec2-xls-r-1b-turkish

wav2vec2-xls-r-1b-turkish is a automatic speech recognition model from Baybars. Use it when you need speech turned into text. It is set up for transformers.

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

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At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: wav2vec2
Access: Public
Created: Mar 2, 2022
Updated: Feb 3, 2022
SHA: c05579f4

Datasets

common_voice

Model card

From the Hugging Face model README

This model is a fine-tuned version of ./checkpoint-10500 on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

Loss: 0.7540
Wer: 0.4647
Cer: 0.1318

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: 0.0002
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.999,0.9999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 120.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Cer	Validation Loss	Wer
1.0779	4.59	500	0.2354	0.8260	0.7395
0.7573	9.17	1000	0.2100	0.7544	0.6960
0.8225	13.76	1500	0.2021	0.6867	0.6672
0.621	18.35	2000	0.1874	0.6824	0.6209
0.6362	22.94	2500	0.1904	0.6712	0.6286
0.624	27.52	3000	0.1820	0.6940	0.6116
0.4781	32.11	3500	0.1735	0.6966	0.5989
0.5685	36.7	4000	0.1769	0.6742	0.5971
0.4384	41.28	4500	0.1767	0.6904	0.5999
0.5509	45.87	5000	0.1692	0.6734	0.5641
0.3665	50.46	5500	0.1680	0.7018	0.5662
0.3914	55.05	6000	0.1631	0.7121	0.5552
0.2467	59.63	6500	0.1563	0.6657	0.5374
0.2576	64.22	7000	0.1554	0.6920	0.5316
0.2711	68.81	7500	0.1495	0.6900	0.5176
0.2626	73.39	8000	0.1454	0.6843	0.5043
0.1377	77.98	8500	0.1470	0.7383	0.5101
0.2005	82.57	9000	0.1430	0.7228	0.5045
0.1355	87.16	9500	0.1375	0.7231	0.4869
0.0431	91.74	10000	0.1350	0.7397	0.4749
0.0586	96.33	10500	0.1339	0.7360	0.4754
0.0896	100.92	11000	0.7187	0.4885	0.1398
0.183	105.5	11500	0.7310	0.4838	0.1392
0.0963	110.09	12000	0.7643	0.4759	0.1362
0.0437	114.68	12500	0.7525	0.4641	0.1328
0.1122	119.27	13000	0.7535	0.4651	0.1317

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.2.dev0
Tokenizers 0.11.0

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Languages: tr
Created: Mar 2, 2022
Updated: Feb 3, 2022