---
language:
- bn
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small bn - Group 4
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: default
      split: test
      args: 'config: bn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 42.212627219456316
---

<!-- 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 bn - Group 4

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2751
- Wer: 42.2126

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.163         | 1.06  | 500  | 0.2064          | 55.6065 |
| 0.0862        | 2.12  | 1000 | 0.1675          | 47.1869 |
| 0.0475        | 3.18  | 1500 | 0.1696          | 44.8561 |
| 0.0239        | 4.24  | 2000 | 0.1848          | 43.2436 |
| 0.0119        | 5.3   | 2500 | 0.2081          | 43.5608 |
| 0.0058        | 6.36  | 3000 | 0.2262          | 43.0718 |
| 0.0024        | 7.42  | 3500 | 0.2427          | 42.4726 |
| 0.0009        | 8.47  | 4000 | 0.2611          | 42.6356 |
| 0.0005        | 9.53  | 4500 | 0.2709          | 42.3492 |
| 0.0004        | 10.59 | 5000 | 0.2751          | 42.2126 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0