| --- |
| language: |
| - ur |
| license: apache-2.0 |
| tags: |
| - automatic-speech-recognition |
| - hf-asr-leaderboard |
| - robust-speech-event |
| datasets: |
| - mozilla-foundation/common_voice_8_0 |
| metrics: |
| - wer |
| - cer |
| model-index: |
| - name: wav2vec2-60-urdu |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Speech Recognition |
| dataset: |
| type: mozilla-foundation/common_voice_7_0 |
| name: Common Voice ur |
| args: ur |
| metrics: |
| - type: wer |
| value: 59.1 |
| name: Test WER |
| args: |
| learning_rate: 0.0003 |
| train_batch_size: 16 |
| eval_batch_size: 8 |
| seed: 42 |
| gradient_accumulation_steps: 2 |
| total_train_batch_size: 32 |
| optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| lr_scheduler_type: linear |
| lr_scheduler_warmup_steps: 200 |
| num_epochs: 50 |
| mixed_precision_training: Native AMP |
| - type: cer |
| value: 33.1 |
| name: Test CER |
| args: |
| learning_rate: 0.0003 |
| train_batch_size: 16 |
| eval_batch_size: 8 |
| seed: 42 |
| gradient_accumulation_steps: 2 |
| total_train_batch_size: 32 |
| optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| lr_scheduler_type: linear |
| lr_scheduler_warmup_steps: 200 |
| num_epochs: 50 |
| mixed_precision_training: Native AMP |
|
|
| --- |
| |
|
|
| **🔴Check out my latest URDU ASR model with `25 WER` here ->** [kingabzpro/whisper-large-v3-turbo-urdu](https://huggingface.co/kingabzpro/whisper-large-v3-turbo-urdu) |
|
|
| --- |
|
|
| # wav2vec2-large-xlsr-53-urdu |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Wer: 0.5913 |
| - Cer: 0.3310 |
| |
| ## Model description |
| 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. |
| |
| ## Training procedure |
| Trained on Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 due to lesser number of samples. |
| |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 200 |
| - num_epochs: 50 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | 12.6045 | 8.33 | 100 | 8.4997 | 0.6978 | 0.3923 | |
| | 1.3367 | 16.67 | 200 | 5.0015 | 0.6515 | 0.3556 | |
| | 0.5344 | 25.0 | 300 | 9.3687 | 0.6393 | 0.3625 | |
| | 0.2922 | 33.33 | 400 | 9.2381 | 0.6236 | 0.3432 | |
| | 0.1867 | 41.67 | 500 | 6.2150 | 0.6035 | 0.3448 | |
| | 0.1166 | 50.0 | 600 | 6.4496 | 0.5913 | 0.3310 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.15.0 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.17.0 |
| - Tokenizers 0.10.3 |
| |
