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