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--- |
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language: |
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- ur |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- hf-asr-leaderboard |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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metrics: |
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- wer |
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- cer |
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model-index: |
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- name: wav2vec2-60-urdu |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_7_0 |
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name: Common Voice ur |
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args: ur |
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metrics: |
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- type: wer |
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value: 59.1 |
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name: Test WER |
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args: |
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learning_rate: 0.0003 |
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train_batch_size: 16 |
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eval_batch_size: 8 |
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seed: 42 |
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gradient_accumulation_steps: 2 |
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total_train_batch_size: 32 |
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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: 200 |
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num_epochs: 50 |
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mixed_precision_training: Native AMP |
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- type: cer |
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value: 33.1 |
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name: Test CER |
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args: |
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learning_rate: 0.0003 |
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train_batch_size: 16 |
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eval_batch_size: 8 |
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seed: 42 |
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gradient_accumulation_steps: 2 |
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total_train_batch_size: 32 |
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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: 200 |
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num_epochs: 50 |
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mixed_precision_training: Native AMP |
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--- |
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# wav2vec2-large-xlsr-53-urdu |
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This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-urdu-urm-60](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-urdu-urm-60) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Wer: 0.5913 |
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- Cer: 0.3310 |
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## Model description |
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The training and valid dataset is 0.58 hours. It was hard to train any model on lower number of so I decided to take vakyansh-wav2vec2-urdu-urm-60 checkpoint and finetune the wav2vec2 model. |
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## Training procedure |
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Trained on Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 due to lesser number of samples. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 200 |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 12.6045 | 8.33 | 100 | 8.4997 | 0.6978 | 0.3923 | |
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| 1.3367 | 16.67 | 200 | 5.0015 | 0.6515 | 0.3556 | |
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| 0.5344 | 25.0 | 300 | 9.3687 | 0.6393 | 0.3625 | |
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| 0.2922 | 33.33 | 400 | 9.2381 | 0.6236 | 0.3432 | |
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| 0.1867 | 41.67 | 500 | 6.2150 | 0.6035 | 0.3448 | |
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| 0.1166 | 50.0 | 600 | 6.4496 | 0.5913 | 0.3310 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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