---
language:
- bn
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- bengaliAI-kaggle
metrics:
- wer
model-index:
- name: whisper-small fintuned-0-10000-50%
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bengaliAI-kaggle
      type: bengaliAI-kaggle
      args: 'config: bn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 90.44179607559889
---

<!-- 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 fintuned-0-10000-50%

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the bengaliAI-kaggle dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6193
- Wer: 90.4418

## 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: 8
- 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: 50
- training_steps: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8424        | 0.4   | 100  | 0.7538          | 103.2021 |
| 0.6195        | 0.8   | 200  | 0.6193          | 90.4418  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3