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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: urdumodel
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results: []
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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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# urdumodel
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4889
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- Wer: 0.3744
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- Cer: 0.1488
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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: 24
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- eval_batch_size: 24
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 96
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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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- num_epochs: 15
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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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| 2.8998 | 1.0 | 508 | 1.0261 | 0.7004 | 0.2832 |
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| 0.7426 | 2.0 | 1016 | 0.6532 | 0.5236 | 0.2026 |
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| 0.5694 | 3.0 | 1524 | 0.5495 | 0.4611 | 0.1799 |
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| 0.4966 | 4.0 | 2032 | 0.5361 | 0.4350 | 0.1729 |
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| 0.4555 | 5.0 | 2540 | 0.5335 | 0.4266 | 0.1684 |
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| 0.4203 | 6.0 | 3048 | 0.5040 | 0.4107 | 0.1641 |
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| 0.3951 | 7.0 | 3556 | 0.5213 | 0.4037 | 0.1579 |
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| 0.3675 | 8.0 | 4064 | 0.4949 | 0.3973 | 0.1563 |
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| 0.3555 | 9.0 | 4572 | 0.4968 | 0.3978 | 0.1581 |
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| 0.3408 | 10.0 | 5080 | 0.4827 | 0.3925 | 0.1561 |
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| 0.3286 | 11.0 | 5588 | 0.5011 | 0.3858 | 0.1524 |
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| 0.3156 | 12.0 | 6096 | 0.4871 | 0.3833 | 0.1524 |
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| 0.3047 | 13.0 | 6604 | 0.4835 | 0.3774 | 0.1499 |
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| 0.2929 | 14.0 | 7112 | 0.4844 | 0.3751 | 0.1489 |
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| 0.2912 | 15.0 | 7620 | 0.4889 | 0.3744 | 0.1488 |
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### Framework versions
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- Transformers 4.21.1
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- Pytorch 1.12.0
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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