transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer bn dataset:mozilla-foundation/common_voice_16_0 base_model:arun100/whisper-base-bn-3 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- bn
license: apache-2.0
base_model: arun100/whisper-base-bn-3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Bengali
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 bn
      type: mozilla-foundation/common_voice_16_0
      config: bn
      split: test
      args: bn
    metrics:
    - name: Wer
      type: wer
      value: 28.818465723515253
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Bengali

This model is a fine-tuned version of [arun100/whisper-base-bn-3](https://huggingface.co/arun100/whisper-base-bn-3) on the mozilla-foundation/common_voice_16_0 bn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2078
- Wer: 28.8185

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1568        | 1.72  | 500  | 0.2145          | 29.8350 |
| 0.1507        | 3.43  | 1000 | 0.2132          | 29.5594 |
| 0.1466        | 5.15  | 1500 | 0.2119          | 29.3576 |
| 0.1463        | 6.86  | 2000 | 0.2106          | 29.2927 |
| 0.1426        | 8.58  | 2500 | 0.2098          | 29.2220 |
| 0.139         | 10.29 | 3000 | 0.2093          | 29.1075 |
| 0.1373        | 12.01 | 3500 | 0.2087          | 29.0878 |
| 0.1362        | 13.72 | 4000 | 0.2084          | 28.9769 |
| 0.1333        | 15.44 | 4500 | 0.2081          | 28.9129 |
| 0.1332        | 17.15 | 5000 | 0.2079          | 28.8945 |
| 0.1363        | 18.87 | 5500 | 0.2078          | 28.8185 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
