---
language:
- bn
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
- openslr
- crblp
metrics:
- wer
model-index:
- name: Whisper Small - Mohammed Rakib
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: bn_in
      split: test
    metrics:
    - type: wer
      value: 10.8
      name: WER
    - type: cer
      value: 6.55
      name: CER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: bn
      split: test
    metrics:
    - type: wer
      value: 8.94
      name: WER
    - type: cer
      value: 4.71
      name: CER
---

<!-- 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 - Mohammed Rakib

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common-voice-11, the google-fleurs, the openslr53 and the crblp speech corpus datasets.
It achieves the following results on the evaluation set:
- Loss: 0.0617
- Cer: 5.4436
- Wer: 9.6538

## 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: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 8000
- training_steps: 40000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer     | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.5361        | 0.13  | 1000  | 0.4043          | 22.6599 | 44.0521 |
| 0.2881        | 0.26  | 2000  | 0.2217          | 16.3939 | 32.4894 |
| 0.2265        | 0.38  | 3000  | 0.1728          | 13.0425 | 25.9637 |
| 0.1974        | 0.51  | 4000  | 0.1430          | 11.3260 | 22.3187 |
| 0.1591        | 0.64  | 5000  | 0.1255          | 10.0167 | 19.5115 |
| 0.1504        | 0.77  | 6000  | 0.1102          | 8.8333  | 17.1919 |
| 0.1259        | 0.89  | 7000  | 0.1003          | 8.1863  | 15.8576 |
| 0.1184        | 1.02  | 8000  | 0.0940          | 7.7868  | 14.9110 |
| 0.1099        | 1.15  | 9000  | 0.0885          | 7.3675  | 13.9444 |
| 0.1075        | 1.28  | 10000 | 0.0830          | 6.9648  | 13.2008 |
| 0.095         | 1.41  | 11000 | 0.0789          | 6.6969  | 12.6776 |
| 0.0943        | 1.53  | 12000 | 0.0766          | 6.3765  | 11.9896 |
| 0.0923        | 1.66  | 13000 | 0.0731          | 6.1784  | 11.7203 |
| 0.0824        | 1.79  | 14000 | 0.0699          | 5.9267  | 11.1632 |
| 0.0756        | 1.92  | 15000 | 0.0683          | 5.6305  | 10.6327 |
| 0.0634        | 2.04  | 16000 | 0.0671          | 5.6905  | 10.6947 |
| 0.0618        | 2.17  | 17000 | 0.0662          | 5.5107  | 10.2926 |
| 0.0679        | 2.3   | 18000 | 0.0643          | 5.4948  | 10.1792 |
| 0.0589        | 2.43  | 19000 | 0.0647          | 5.5201  | 10.1881 |
| 0.0623        | 2.56  | 20000 | 0.0633          | 5.2731  | 9.8449  |
| 0.0558        | 2.68  | 21000 | 0.0623          | 5.4211  | 10.0267 |
| 0.0564        | 2.81  | 22000 | 0.0617          | 5.4553  | 9.9893  |
| 0.0552        | 2.94  | 23000 | 0.0607          | 5.3860  | 9.7778  |
| 0.0403        | 3.07  | 24000 | 0.0621          | 5.7297  | 10.0382 |
| 0.0406        | 3.19  | 25000 | 0.0617          | 5.4436  | 9.6538  |
| 0.041         | 3.32  | 26000 | 0.0611          | 6.0867  | 10.3834 |
| 0.0388        | 3.45  | 27000 | 0.0614          | 6.1641  | 10.3890 |
| 0.0383        | 3.58  | 28000 | 0.0611          | 6.1460  | 10.3537 |
| 0.0401        | 3.71  | 29000 | 0.0603          | 6.9576  | 11.0697 |
| 0.0343        | 3.83  | 30000 | 0.0613          | 7.1918  | 11.2243 |
| 0.0357        | 3.96  | 31000 | 0.0603          | 7.3128  | 11.3313 |
| 0.0313        | 4.09  | 32000 | 0.0624          | 7.3871  | 11.3861 |
| 0.0281        | 4.22  | 33000 | 0.0626          | 7.8705  | 11.8248 |
| 0.0298        | 4.34  | 34000 | 0.0629          | 8.3360  | 12.2368 |
| 0.0282        | 4.47  | 35000 | 0.0627          | 8.7840  | 12.6270 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.2.dev0
- Tokenizers 0.13.2