wav2vec2-xls-r-300m-cv7-turkish

Model description

This ASR model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on Turkish language.

Training and evaluation data

The following datasets were used for finetuning:

Common Voice 7.0 TR All validated split except test split was used for training.

MediaSpeech

Training procedure

To support both of the datasets above, custom pre-processing and loading steps was performed and wav2vec2-turkish repo was used for that purpose.

Training hyperparameters

The following hypermaters were used for finetuning:

learning_rate 2e-4

num_train_epochs 10

warmup_steps 500

freeze_feature_extractor

mask_time_prob 0.1

mask_feature_prob 0.05

feat_proj_dropout 0.05

attention_dropout 0.05

final_dropout 0.05

activation_dropout 0.05

per_device_train_batch_size 8

per_device_eval_batch_size 8

gradient_accumulation_steps 8

Framework versions

Transformers 4.16.0.dev0

Pytorch 1.10.1

Datasets 1.17.0

Tokenizers 0.10.3

Language Model

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

Evaluation Commands

Please install unicode_tr package before running evaluation. It is used for Turkish text processing. 1. To evaluate on mozilla-foundation/common_voice_7_0 with split test 2. To evaluate on speech-recognition-community-v2/dev_data

Evaluation results:

| Dataset | WER | CER | |---|---|---| |Common Voice 7 TR test split| 8.62 | 2.26 | |Speech Recognition Community dev data| 30.87 | 10.69 |