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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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base_model: facebook/w2v-bert-2.0 |
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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: 0.6273224043715847 |
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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 is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) 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: 1.1498 |
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- Wer: 0.6273 |
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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-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: 500 |
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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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| 3.5968 | 0.1695 | 50 | 3.1737 | 1.0 | |
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| 3.1414 | 0.3390 | 100 | 2.9666 | 1.0 | |
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| 2.3694 | 0.5085 | 150 | 1.0788 | 0.6525 | |
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| 0.7692 | 0.6780 | 200 | 0.5647 | 0.4186 | |
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| 0.5488 | 0.8475 | 250 | 0.4491 | 0.3486 | |
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| 0.5568 | 1.0169 | 300 | 0.5883 | 0.7388 | |
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| 0.7925 | 1.1864 | 350 | 1.0338 | 0.7967 | |
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| 1.4791 | 1.3559 | 400 | 1.1474 | 0.6251 | |
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| 1.2758 | 1.5254 | 450 | 1.1359 | 0.6251 | |
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| 1.2763 | 1.6949 | 500 | 1.1497 | 0.6273 | |
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| 1.2789 | 1.8644 | 550 | 1.1498 | 0.6273 | |
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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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