--- language: - ur license: apache-2.0 tags: - automatic-speech-recognition - robust-speech-event datasets: - mozilla-foundation/common_voice_8_0 metrics: - wer - cer model-index: - name: wav2vec2-urdu-V8-Abid results: - task: type: automatic-speech-recognition # Required. Example: automatic-speech-recognition name: Speech Recognition # Optional. Example: Speech Recognition dataset: type: mozilla-foundation/common_voice_8_0 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets name: Common Voice ur # Required. Example: Common Voice zh-CN args: ur # Optional. Example: zh-CN metrics: - type: wer # Required. Example: wer value: 44.63 # Required. Example: 20.90 name: Test WER # Optional. Example: Test WER args: - learning_rate: 7.5e-05 - 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 AMPP # Optional. Example for BLEU: max_order - type: cer # Required. Example: wer value: 18.82 # Required. Example: 20.90 name: Test CER # Optional. Example: Test WER args: - learning_rate: 7.5e-05 - 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 AMPP --- # wav2vec2-60-Urdu-V8 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: - Loss: 11.4832 - Wer: 0.5729 - Cer: 0.3170 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 7.5e-05 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 19.671 | 8.33 | 100 | 7.7671 | 0.8795 | 0.4492 | | 2.085 | 16.67 | 200 | 9.2759 | 0.6201 | 0.3320 | | 0.6633 | 25.0 | 300 | 8.7025 | 0.5738 | 0.3104 | | 0.388 | 33.33 | 400 | 10.2286 | 0.5852 | 0.3128 | | 0.2822 | 41.67 | 500 | 11.1953 | 0.5738 | 0.3174 | | 0.2293 | 50.0 | 600 | 11.4832 | 0.5729 | 0.3170 | ### Framework versions - Transformers 4.16.2 - Pytorch 1.10.0+cu111 - Datasets 1.18.3 - Tokenizers 0.11.0