---
language:
- bn
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Base Bn - Raiyan Ahmed
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1
      type: mozilla-foundation/common_voice_16_1
      config: bn
      split: None
      args: 'config: bn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 33.449797070760546
---

<!-- 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 Base Bn - Raiyan Ahmed

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1074
- Wer: 33.4498

## 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: 3e-05
- train_batch_size: 26
- eval_batch_size: 46
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2369        | 0.6365 | 1000  | 0.2433          | 62.1881 |
| 0.1242        | 1.2731 | 2000  | 0.1734          | 49.4369 |
| 0.1022        | 1.9096 | 3000  | 0.1197          | 39.0531 |
| 0.046         | 2.5461 | 4000  | 0.1067          | 34.5497 |
| 0.0702        | 2.6247 | 5000  | 0.1210          | 38.4777 |
| 0.1028        | 1.5748 | 6000  | 0.1484          | 44.2750 |
| 0.0772        | 1.8373 | 7000  | 0.1323          | 40.2388 |
| 0.0648        | 2.0997 | 8000  | 0.1205          | 39.1165 |
| 0.0367        | 2.3622 | 9000  | 0.1154          | 35.6332 |
| 0.0249        | 2.6247 | 10000 | 0.1074          | 33.4498 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1