wav2vec2-xls-r-300m-cv8-turkish

Baybars/wav2vec2-xls-r-300m-cv8-turkish

wav2vec2-xls-r-300m-cv8-turkish is a automatic speech recognition model from Baybars. Use it when you need speech turned into text. 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: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Mar 2, 2022
Updated: Mar 23, 2022
SHA: 2362365a

Datasets

common_voice

Model card

From the Hugging Face model README

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

Loss: 0.4164
Wer: 0.3098
Cer: 0.0764

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Language Model

N-gram language model is trained by mpoyraz on a Turkish Wikipedia articles using KenLM and ngram-lm-wiki repo was used to generate arpa LM and convert it into binary format.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 64
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 100.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.6356	9.09	500	0.5055	0.5536	0.1381
0.3847	18.18	1000	0.4002	0.4247	0.1065
0.3377	27.27	1500	0.4193	0.4167	0.1078
0.2175	36.36	2000	0.4351	0.3861	0.0974
0.2074	45.45	2500	0.3962	0.3622	0.0916
0.159	54.55	3000	0.4062	0.3526	0.0888
0.1882	63.64	3500	0.3991	0.3445	0.0850
0.1766	72.73	4000	0.4214	0.3396	0.0847
0.116	81.82	4500	0.4182	0.3265	0.0812
0.0718	90.91	5000	0.4259	0.3191	0.0781
0.019	100.0	5500	0.4164	0.3098	0.0764

Evaluation Commands

Please install unicode_tr package before running evaluation. It is used for Turkish text processing.

To evaluate on mozilla-foundation/common_voice_7_0 with split test

python eval.py --model_id Baybars/wav2vec2-xls-r-300m-cv8-turkish --dataset mozilla-foundation/common_voice_8_0 --config tr --split test

To evaluate on speech-recognition-community-v2/dev_data

python eval.py --model_id Baybars/wav2vec2-xls-r-300m-cv8-turkish --dataset speech-recognition-community-v2/dev_data --config tr --split validation --chunk_length_s 5.0 --stride_length_s 1.0

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
License: apache-2.0
Languages: tr
Created: Mar 2, 2022
Updated: Mar 23, 2022