---
language:
 - bn
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper small by ehzawad
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: bn
      split: test
      args: 'config: lt, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 31.32744623273038

---
# Whisper small by ehzawad

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1104
- Wer: 31.3274

## 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: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2424        | 0.27  | 500  | 0.2407          | 63.1783 |
| 0.1559        | 0.53  | 1000 | 0.1633          | 48.0380 |
| 0.1255        | 0.8   | 1500 | 0.1394          | 42.6625 |
| 0.0899        | 1.07  | 2000 | 0.1231          | 38.6982 |
| 0.0872        | 1.34  | 2500 | 0.1172          | 37.3415 |
| 0.0755        | 1.6   | 3000 | 0.1091          | 35.4971 |
| 0.0786        | 1.87  | 3500 | 0.1042          | 34.6567 |
| 0.0499        | 2.14  | 4000 | 0.1047          | 33.2752 |
| 0.0468        | 2.4   | 4500 | 0.1027          | 32.7874 |
| 0.0436        | 2.67  | 5000 | 0.1019          | 32.2877 |
| 0.0379        | 2.94  | 5500 | 0.1000          | 31.7168 |
| 0.025         | 3.2   | 6000 | 0.1062          | 31.6455 |
| 0.0282        | 3.47  | 6500 | 0.1050          | 31.4699 |
| 0.0249        | 3.74  | 7000 | 0.1060          | 31.3737 |
| 0.0231        | 4.01  | 7500 | 0.1049          | 31.1969 |
| 0.0183        | 4.27  | 8000 | 0.1104          | 31.3274 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3