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README.md
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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: null
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split: None
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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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<!-- 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 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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