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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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<!-- 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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# wav2vec2-large-xls-r-300m-pashto-colab-test-6 |
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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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## 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: 0.9 |
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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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### Training results |
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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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### Framework versions |
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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 |
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