readme: ---
  language:
  - bn
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Bengali
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 bn
        type: mozilla-foundation/common_voice_11_0
        config: bn
        split: test
        args: bn
      metrics:
      - name: Wer
        type: wer
        value: 14.462277064693396
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # Whisper Small Bengali
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 bn dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3377
  - Wer: 14.4623
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 4
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 5000
  - training_steps: 60000
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer     |
  |:-------------:|:------:|:-----:|:---------------:|:-------:|
  | 0.2431        | 1.92   | 1000  | 0.2604          | 33.5683 |
  | 0.1403        | 3.83   | 2000  | 0.1703          | 23.7591 |
  | 0.0799        | 5.75   | 3000  | 0.1429          | 19.5394 |
  | 0.0411        | 7.66   | 4000  | 0.1568          | 19.0023 |
  | 0.0244        | 9.58   | 5000  | 0.1684          | 18.3154 |
  | 0.0139        | 11.49  | 6000  | 0.1856          | 17.7401 |
  | 0.0085        | 13.41  | 7000  | 0.2062          | 17.5263 |
  | 0.0063        | 15.33  | 8000  | 0.2146          | 17.2952 |
  | 0.0041        | 17.24  | 9000  | 0.2202          | 16.9966 |
  | 0.0033        | 19.16  | 10000 | 0.2163          | 16.4749 |
  | 0.0027        | 21.07  | 11000 | 0.2267          | 16.5334 |
  | 0.0031        | 22.99  | 12000 | 0.2313          | 16.4263 |
  | 0.0033        | 24.9   | 13000 | 0.2289          | 16.3544 |
  | 0.0025        | 26.82  | 14000 | 0.2384          | 16.0087 |
  | 0.0023        | 28.74  | 15000 | 0.2343          | 16.1089 |
  | 0.0027        | 30.65  | 16000 | 0.2389          | 16.1495 |
  | 0.0022        | 32.57  | 17000 | 0.2461          | 15.9631 |
  | 0.0016        | 34.48  | 18000 | 0.2364          | 15.9040 |
  | 0.0015        | 36.4   | 19000 | 0.2415          | 15.7161 |
  | 0.0009        | 38.31  | 20000 | 0.2411          | 15.3724 |
  | 0.0013        | 40.23  | 21000 | 0.2425          | 15.5817 |
  | 0.0013        | 42.15  | 22000 | 0.2469          | 15.5112 |
  | 0.001         | 44.06  | 23000 | 0.2549          | 15.5474 |
  | 0.0015        | 45.98  | 24000 | 0.2481          | 15.3624 |
  | 0.0013        | 47.89  | 25000 | 0.2517          | 15.5316 |
  | 0.0007        | 49.81  | 26000 | 0.2559          | 15.2305 |
  | 0.0006        | 51.72  | 27000 | 0.2567          | 15.4066 |
  | 0.0008        | 53.64  | 28000 | 0.2538          | 15.2464 |
  | 0.0009        | 55.56  | 29000 | 0.2468          | 15.1284 |
  | 0.0005        | 57.47  | 30000 | 0.2660          | 15.0138 |
  | 0.0003        | 59.39  | 31000 | 0.2594          | 14.9384 |
  | 0.0004        | 61.3   | 32000 | 0.2580          | 14.8814 |
  | 0.0006        | 63.22  | 33000 | 0.2642          | 14.9374 |
  | 0.0005        | 65.13  | 34000 | 0.2650          | 15.1155 |
  | 0.0003        | 67.05  | 35000 | 0.2660          | 14.9939 |
  | 0.0004        | 68.97  | 36000 | 0.2625          | 15.1031 |
  | 0.0002        | 70.88  | 37000 | 0.2782          | 14.8139 |
  | 0.0003        | 72.8   | 38000 | 0.2647          | 15.0768 |
  | 0.0004        | 74.71  | 39000 | 0.2665          | 14.8680 |
  | 0.0004        | 76.63  | 40000 | 0.2711          | 14.7966 |
  | 0.0001        | 78.54  | 41000 | 0.2742          | 14.8075 |
  | 0.0002        | 80.46  | 42000 | 0.2703          | 14.9364 |
  | 0.0001        | 82.38  | 43000 | 0.2733          | 14.7604 |
  | 0.0003        | 84.29  | 44000 | 0.2741          | 14.8209 |
  | 0.0           | 86.21  | 45000 | 0.2792          | 14.6046 |
  | 0.0           | 88.12  | 46000 | 0.2764          | 14.7356 |
  | 0.0           | 90.04  | 47000 | 0.2830          | 14.6874 |
  | 0.0           | 91.95  | 48000 | 0.2887          | 14.5630 |
  | 0.0           | 93.87  | 49000 | 0.2951          | 14.5803 |
  | 0.0           | 95.79  | 50000 | 0.3008          | 14.5476 |
  | 0.0           | 97.7   | 51000 | 0.3060          | 14.5188 |
  | 0.0           | 99.62  | 52000 | 0.3110          | 14.5248 |
  | 0.0        