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update model card README.md

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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-xls-r-300m-urdu-colab
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.42745782431646306
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+ ---
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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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+
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+ # wav2vec2-large-xls-r-300m-urdu-colab
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: inf
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+ - Wer: 0.4275
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 6.0615 | 3.09 | 400 | inf | 0.9448 |
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+ | 0.8996 | 6.18 | 800 | inf | 0.5206 |
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+ | 0.4001 | 9.27 | 1200 | inf | 0.4890 |
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+ | 0.2377 | 12.36 | 1600 | inf | 0.4609 |
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+ | 0.1599 | 15.44 | 2000 | inf | 0.4407 |
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+ | 0.1156 | 18.53 | 2400 | inf | 0.4275 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 1.18.3
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+ - Tokenizers 0.13.3