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--- |
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language: |
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- ps |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Pashto - Augmented |
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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: google/fleurs |
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type: google/fleurs |
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config: ps_af |
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split: test |
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args: ps_af |
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metrics: |
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- name: Wer |
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type: wer |
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value: 57.611985472154956 |
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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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# Whisper Base Pashto - Augmented |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8723 |
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- Wer: 57.6120 |
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- Cer: 26.6468 |
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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: 1e-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: 4 |
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- total_train_batch_size: 64 |
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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: 30 |
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- training_steps: 1000 |
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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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| 0.9708 | 2.38 | 100 | 0.8821 | 64.0133 | 27.3253 | |
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| 0.7477 | 4.75 | 200 | 0.8062 | 59.9576 | 26.4079 | |
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| 0.6229 | 7.14 | 300 | 0.7855 | 58.3081 | 26.3193 | |
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| 0.4833 | 9.52 | 400 | 0.7870 | 57.5288 | 24.8855 | |
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| 0.4084 | 11.89 | 500 | 0.7980 | 56.5224 | 25.2214 | |
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| 0.3323 | 14.28 | 600 | 0.8201 | 56.6662 | 25.3317 | |
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| 0.283 | 16.66 | 700 | 0.8406 | 57.7406 | 26.8674 | |
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| 0.2598 | 19.05 | 800 | 0.8538 | 57.2866 | 26.0386 | |
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| 0.2235 | 21.42 | 900 | 0.8697 | 58.2703 | 26.6819 | |
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| 0.2202 | 23.8 | 1000 | 0.8723 | 57.6120 | 26.6468 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.1.dev0 |
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- Tokenizers 0.13.2 |
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