---
language:
- bn
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper tiny bn - Raiyan
  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: None
      args: 'config: bn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 44.349095570431565
---

<!-- 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 tiny bn - Raiyan

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice_13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1734
- Wer: 44.3491

## 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: 6e-05
- train_batch_size: 24
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 3000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.261         | 1.0661 | 500  | 0.2417          | 63.3469 |
| 0.1926        | 2.1322 | 1000 | 0.1941          | 54.3987 |
| 0.1367        | 3.1983 | 1500 | 0.1729          | 49.3116 |
| 0.0994        | 4.2644 | 2000 | 0.1622          | 46.2280 |
| 0.0564        | 5.3305 | 2500 | 0.1669          | 45.0802 |
| 0.0394        | 6.3966 | 3000 | 0.1734          | 44.3491 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1