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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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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Bn - Raiyan Ahmed |
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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 16.1 |
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type: mozilla-foundation/common_voice_16_1 |
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config: bn |
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split: None |
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args: 'config: bn, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 33.449797070760546 |
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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 Bn - Raiyan Ahmed |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 16.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1074 |
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- Wer: 33.4498 |
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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: 3e-05 |
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- train_batch_size: 26 |
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- eval_batch_size: 46 |
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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: 500 |
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- training_steps: 10000 |
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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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| 0.2369 | 0.6365 | 1000 | 0.2433 | 62.1881 | |
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| 0.1242 | 1.2731 | 2000 | 0.1734 | 49.4369 | |
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| 0.1022 | 1.9096 | 3000 | 0.1197 | 39.0531 | |
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| 0.046 | 2.5461 | 4000 | 0.1067 | 34.5497 | |
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| 0.0702 | 2.6247 | 5000 | 0.1210 | 38.4777 | |
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| 0.1028 | 1.5748 | 6000 | 0.1484 | 44.2750 | |
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| 0.0772 | 1.8373 | 7000 | 0.1323 | 40.2388 | |
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| 0.0648 | 2.0997 | 8000 | 0.1205 | 39.1165 | |
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| 0.0367 | 2.3622 | 9000 | 0.1154 | 35.6332 | |
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| 0.0249 | 2.6247 | 10000 | 0.1074 | 33.4498 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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