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--- |
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language: |
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- bn |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper small by ehzawad |
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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: Common Voice 13.0 |
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type: mozilla-foundation/common_voice_13_0 |
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config: bn |
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split: test |
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args: 'config: lt, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 31.32744623273038 |
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--- |
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# Whisper small by ehzawad |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1104 |
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- Wer: 31.3274 |
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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: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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- training_steps: 8000 |
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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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| 0.2424 | 0.27 | 500 | 0.2407 | 63.1783 | |
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| 0.1559 | 0.53 | 1000 | 0.1633 | 48.0380 | |
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| 0.1255 | 0.8 | 1500 | 0.1394 | 42.6625 | |
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| 0.0899 | 1.07 | 2000 | 0.1231 | 38.6982 | |
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| 0.0872 | 1.34 | 2500 | 0.1172 | 37.3415 | |
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| 0.0755 | 1.6 | 3000 | 0.1091 | 35.4971 | |
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| 0.0786 | 1.87 | 3500 | 0.1042 | 34.6567 | |
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| 0.0499 | 2.14 | 4000 | 0.1047 | 33.2752 | |
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| 0.0468 | 2.4 | 4500 | 0.1027 | 32.7874 | |
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| 0.0436 | 2.67 | 5000 | 0.1019 | 32.2877 | |
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| 0.0379 | 2.94 | 5500 | 0.1000 | 31.7168 | |
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| 0.025 | 3.2 | 6000 | 0.1062 | 31.6455 | |
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| 0.0282 | 3.47 | 6500 | 0.1050 | 31.4699 | |
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| 0.0249 | 3.74 | 7000 | 0.1060 | 31.3737 | |
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| 0.0231 | 4.01 | 7500 | 0.1049 | 31.1969 | |
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| 0.0183 | 4.27 | 8000 | 0.1104 | 31.3274 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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