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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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- robust-speech-event |
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- hf-asr-leaderboard |
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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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base_model: Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 |
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model-index: |
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- name: wav2vec2-urdu-V8-Abid |
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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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name: Common Voice ur |
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type: mozilla-foundation/common_voice_8_0 |
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args: ur |
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metrics: |
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- type: wer |
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value: 44.63 |
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name: Test WER |
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- type: cer |
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value: 18.82 |
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name: Test CER |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-60-Urdu-V8 |
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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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- Loss: 11.4832 |
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- Wer: 0.5729 |
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- Cer: 0.3170 |
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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-05 |
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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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| 19.671 | 8.33 | 100 | 7.7671 | 0.8795 | 0.4492 | |
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| 2.085 | 16.67 | 200 | 9.2759 | 0.6201 | 0.3320 | |
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| 0.6633 | 25.0 | 300 | 8.7025 | 0.5738 | 0.3104 | |
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| 0.388 | 33.33 | 400 | 10.2286 | 0.5852 | 0.3128 | |
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| 0.2822 | 41.67 | 500 | 11.1953 | 0.5738 | 0.3174 | |
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| 0.2293 | 50.0 | 600 | 11.4832 | 0.5729 | 0.3170 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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