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--- |
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base_model: Shehryar718/URDU-ASR |
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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-25-EPOCH |
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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: 0.47599520290920344 |
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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-25-EPOCH |
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This model is a fine-tuned version of [Shehryar718/URDU-ASR](https://huggingface.co/Shehryar718/URDU-ASR) 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: 0.6782 |
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- Wer: 0.4760 |
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- Cer: 0.1986 |
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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: 7.5e-05 |
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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=(0.9,0.99) 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: 25 |
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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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| 5.3707 | 1.0 | 341 | 1.3583 | 0.8266 | 0.3484 | |
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| 0.4814 | 2.0 | 683 | 0.7213 | 0.5187 | 0.2196 | |
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| 0.2821 | 3.0 | 1024 | 0.6354 | 0.4917 | 0.2066 | |
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| 0.2368 | 4.0 | 1366 | 0.6730 | 0.5122 | 0.2181 | |
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| 0.2105 | 5.0 | 1707 | 0.6430 | 0.4871 | 0.2076 | |
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| 0.1965 | 6.0 | 2049 | 0.6397 | 0.4902 | 0.2136 | |
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| 0.1879 | 7.0 | 2390 | 0.6397 | 0.4698 | 0.1951 | |
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| 0.1743 | 8.0 | 2732 | 0.6636 | 0.4739 | 0.1996 | |
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| 0.1632 | 9.0 | 3073 | 0.6752 | 0.4782 | 0.1996 | |
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| 0.1572 | 10.0 | 3415 | 0.6859 | 0.4874 | 0.2072 | |
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| 0.1586 | 11.0 | 3756 | 0.6761 | 0.4844 | 0.2069 | |
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| 0.1595 | 12.0 | 4098 | 0.6846 | 0.4746 | 0.1959 | |
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| 0.1534 | 13.0 | 4439 | 0.6750 | 0.4830 | 0.2034 | |
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| 0.16 | 14.0 | 4781 | 0.6653 | 0.4826 | 0.2038 | |
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| 0.1752 | 15.0 | 5122 | 0.6536 | 0.4727 | 0.1946 | |
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| 0.1739 | 16.0 | 5464 | 0.6753 | 0.4738 | 0.1912 | |
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| 0.1709 | 17.0 | 5805 | 0.6600 | 0.4730 | 0.1996 | |
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| 0.1676 | 18.0 | 6147 | 0.6691 | 0.4678 | 0.1919 | |
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| 0.1636 | 19.0 | 6488 | 0.6638 | 0.4772 | 0.1990 | |
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| 0.1593 | 20.0 | 6830 | 0.6787 | 0.4764 | 0.1976 | |
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| 0.1588 | 21.0 | 7171 | 0.6699 | 0.4772 | 0.1974 | |
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| 0.1525 | 22.0 | 7513 | 0.6827 | 0.4738 | 0.1962 | |
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| 0.1554 | 23.0 | 7854 | 0.6740 | 0.4736 | 0.1970 | |
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| 0.1522 | 24.0 | 8196 | 0.6791 | 0.4768 | 0.1989 | |
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| 0.1502 | 24.96 | 8525 | 0.6782 | 0.4760 | 0.1986 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.4 |
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- Tokenizers 0.14.1 |
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