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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_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v2-bert-urdu |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: ur |
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split: test[:100] |
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args: ur |
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metrics: |
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- type: wer |
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value: 0.3300546448087432 |
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name: Wer |
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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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# w2v2-bert-urdu |
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This model was trained from scratch on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4246 |
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- Wer: 0.3301 |
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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: 5e-06 |
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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: 100 |
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- num_epochs: 2 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.8145 | 0.1695 | 50 | 0.4620 | 0.3421 | |
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| 0.4364 | 0.3390 | 100 | 0.3969 | 0.2874 | |
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| 0.418 | 0.5085 | 150 | 0.3697 | 0.2820 | |
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| 0.402 | 0.6780 | 200 | 0.3627 | 0.2842 | |
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| 0.3698 | 0.8475 | 250 | 0.3314 | 0.2710 | |
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| 0.3779 | 1.0169 | 300 | 0.3292 | 0.2852 | |
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| 0.3167 | 1.1864 | 350 | 0.3230 | 0.2820 | |
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| 0.3578 | 1.3559 | 400 | 0.3825 | 0.2940 | |
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| 0.4189 | 1.5254 | 450 | 0.4225 | 0.3104 | |
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| 0.4803 | 1.6949 | 500 | 0.4248 | 0.3311 | |
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| 0.4612 | 1.8644 | 550 | 0.4246 | 0.3301 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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