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--- |
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license: apache-2.0 |
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base_model: steja/whisper-small-persian |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: pashto-asr-cws-v1 |
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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: fleurs |
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type: fleurs |
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config: ps_af |
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split: None |
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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: 49.37953995157385 |
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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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# pashto-asr-cws-v1 |
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This model is a fine-tuned version of [steja/whisper-small-persian](https://huggingface.co./steja/whisper-small-persian) on the fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7501 |
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- Wer: 49.3795 |
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- Cer: 20.8766 |
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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: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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| 0.7899 | 0.8065 | 100 | 0.8629 | 75.8323 | 47.9045 | |
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| 0.5051 | 1.6129 | 200 | 0.6860 | 52.9888 | 23.1242 | |
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| 0.3555 | 2.4194 | 300 | 0.6612 | 51.6798 | 22.9404 | |
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| 0.257 | 3.2258 | 400 | 0.6565 | 49.2660 | 21.0588 | |
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| 0.2174 | 4.0323 | 500 | 0.6560 | 47.1777 | 19.8523 | |
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| 0.1626 | 4.8387 | 600 | 0.6787 | 48.7591 | 20.4305 | |
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| 0.1268 | 5.6452 | 700 | 0.7062 | 49.4401 | 21.0137 | |
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| 0.0871 | 6.4516 | 800 | 0.7279 | 49.2433 | 20.7062 | |
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| 0.0685 | 7.2581 | 900 | 0.7443 | 49.3795 | 21.2276 | |
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| 0.0662 | 8.0645 | 1000 | 0.7501 | 49.3795 | 20.8766 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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