--- language: - tr license: apache-2.0 tags: - automatic-speech-recognition - common_voice - generated_from_trainer - hf-asr-leaderboard - robust-speech-event - tr datasets: - mozilla-foundation/common_voice_7_0 model-index: - name: Wav2Vec2 Base Turkish by Cahya results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 6.1 type: mozilla-foundation/common_voice_7_0 args: tr metrics: - name: Test WER type: wer value: 9.437 - name: Test CER type: cer value: 3.325 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7 type: mozilla-foundation/common_voice_7_0 args: tr metrics: - name: Test WER type: wer value: 8.147 - name: Test CER type: cer value: 2.802 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: tr metrics: - name: Test WER type: wer value: 28.011 - name: Test CER type: cer value: 10.66 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: tr metrics: - name: Test WER type: wer value: 33.62 --- # This model is a fine-tuned version of [cahya/wav2vec2-base-turkish-artificial-cv](https://huggingface.co/cahya/wav2vec2-base-turkish-artificial-cv) on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set: | | Dataset | WER | CER | |---|-------------------------------|---------|----------| | 1 | Common Voice 6.1 | 9.437 | 3.325 | | 2 | Common Voice 7.0 | 8.147 | 2.802 | | 3 | Common Voice 8.0 | 8.335 | 2.336 | | 4 | Speech Recognition Community | 28.011 | 10.66 | ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data The following datasets were used for finetuning: - [Common Voice 7.0 TR](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) 'train', 'validation' and 'other' split were used for training. - [Media Speech](https://www.openslr.org/108/) - [Magic Hub](https://magichub.com/) ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 7.5e-06 - train_batch_size: 6 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.1224 | 3.45 | 500 | 0.1641 | 0.1396 | ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.18.2 - Tokenizers 0.10.3