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 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- bn
license: apache-2.0
base_model: arun100/whisper-base-bn
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: 29.92358146984869
---

<!-- 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 Bengali

This model is a fine-tuned version of [arun100/whisper-base-bn](https://huggingface.co/arun100/whisper-base-bn) on the mozilla-foundation/common_voice_16_0 bn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2151
- Wer: 29.9236

## 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-06
- 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: 8500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2476        | 1.72  | 500  | 0.2751          | 36.1695 |
| 0.2284        | 3.43  | 1000 | 0.2622          | 35.1668 |
| 0.213         | 5.15  | 1500 | 0.2524          | 34.2022 |
| 0.2048        | 6.86  | 2000 | 0.2447          | 33.5266 |
| 0.1948        | 8.58  | 2500 | 0.2382          | 32.7495 |
| 0.1852        | 10.29 | 3000 | 0.2334          | 32.2322 |
| 0.1789        | 12.01 | 3500 | 0.2295          | 31.7244 |
| 0.1738        | 13.72 | 4000 | 0.2260          | 31.2341 |
| 0.166         | 15.44 | 4500 | 0.2236          | 30.9562 |
| 0.1629        | 17.15 | 5000 | 0.2214          | 30.8171 |
| 0.1636        | 18.87 | 5500 | 0.2194          | 30.4368 |
| 0.1578        | 20.58 | 6000 | 0.2181          | 30.2520 |
| 0.1628        | 22.3  | 6500 | 0.2170          | 30.1858 |
| 0.1566        | 24.01 | 7000 | 0.2161          | 30.0694 |
| 0.1564        | 25.73 | 7500 | 0.2156          | 29.9943 |
| 0.1545        | 27.44 | 8000 | 0.2153          | 29.9294 |
| 0.1548        | 29.16 | 8500 | 0.2151          | 29.9236 |


### Framework versions

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