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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: URDU-ASR |
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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_13_0 |
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type: common_voice_13_0 |
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config: ur |
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split: test |
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args: ur |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.49680838717165077 |
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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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# URDU-ASR |
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This model was trained from scratch on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6632 |
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- Wer: 0.4968 |
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- Cer: 0.2099 |
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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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More information needed |
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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: 0.0003 |
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- train_batch_size: 8 |
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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: 16 |
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- optimizer: Adam with betas=(0.85,0.9) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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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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| 1.9625 | 1.0 | 341 | 0.7371 | 0.5348 | 0.2190 | |
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| 0.2156 | 2.0 | 683 | 0.7057 | 0.5103 | 0.2169 | |
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| 0.2451 | 3.0 | 1024 | 0.6654 | 0.5161 | 0.2214 | |
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| 0.199 | 4.0 | 1366 | 0.6707 | 0.5089 | 0.2153 | |
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| 0.1657 | 4.99 | 1705 | 0.6632 | 0.4968 | 0.2099 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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