---
language:
- bn
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Bn - Raiyan Ahmed
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: bn
      split: None
      args: 'config: bn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 33.54106242324475
---

<!-- 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 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2026
- Wer: 33.5411

## 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: 3.75e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 16000
- 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 |
| 0.0777        | 3.1827  | 5000  | 0.1440          | 43.2194 |
| 0.0649        | 3.8192  | 6000  | 0.1266          | 38.6232 |
| 0.0367        | 4.4558  | 7000  | 0.1288          | 38.0392 |
| 0.0126        | 5.0923  | 8000  | 0.1382          | 35.0226 |
| 0.0108        | 5.7288  | 9000  | 0.1416          | 34.5340 |
| 0.0038        | 6.3654  | 10000 | 0.1611          | 33.3921 |
| 0.0023        | 7.0019  | 11000 | 0.1744          | 33.4875 |
| 0.0133        | 7.6384  | 12000 | 0.1625          | 36.0534 |
| 0.0066        | 8.2750  | 13000 | 0.1801          | 35.3936 |
| 0.004         | 8.9115  | 14000 | 0.1781          | 34.1577 |
| 0.0009        | 9.5481  | 15000 | 0.1918          | 33.6939 |
| 0.0003        | 10.1846 | 16000 | 0.2026          | 33.5411 |


### Framework versions

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