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update model card README.md

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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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+ - 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-pashto-colab-test-6
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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: 1.0
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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-pashto-colab-test-6
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+
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+ This model is a fine-tuned version of [rsd16/wav2vec2-large-xlsr-53-fine-tuned-farsi](https://huggingface.co/rsd16/wav2vec2-large-xlsr-53-fine-tuned-farsi) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Wer: 1.0
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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: 0.9
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 10
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+ - total_train_batch_size: 10
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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: 10
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+ - num_epochs: 15
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+ - mixed_precision_training: Native AMP
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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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+ | 1860014104903.68 | 0.96 | 100 | nan | 1.0 |
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+ | 0.0 | 1.91 | 200 | nan | 1.0 |
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+ | 0.0 | 2.87 | 300 | nan | 1.0 |
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+ | 0.0 | 3.82 | 400 | nan | 1.0 |
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+ | 0.0 | 4.78 | 500 | nan | 1.0 |
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+ | 0.0 | 5.73 | 600 | nan | 1.0 |
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+ | 0.0 | 6.69 | 700 | nan | 1.0 |
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+ | 0.0 | 7.64 | 800 | nan | 1.0 |
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+ | 0.0 | 8.6 | 900 | nan | 1.0 |
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+ | 0.0 | 9.55 | 1000 | nan | 1.0 |
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+ | 0.0 | 10.51 | 1100 | nan | 1.0 |
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+ | 0.0 | 11.46 | 1200 | nan | 1.0 |
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+ | 0.0 | 12.42 | 1300 | nan | 1.0 |
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+ | 0.0 | 13.37 | 1400 | nan | 1.0 |
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+ | 0.0 | 14.33 | 1500 | nan | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3