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-hi-1 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- bn
license: apache-2.0
base_model: arun100/whisper-base-hi-1
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: 36.204844612672595
---

<!-- 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-hi-1](https://huggingface.co/arun100/whisper-base-hi-1) on the mozilla-foundation/common_voice_16_0 bn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2754
- Wer: 36.2048

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.693         | 1.04  | 500  | 0.6937          | 69.6782 |
| 0.3979        | 3.03  | 1000 | 0.4168          | 48.0703 |
| 0.3429        | 5.01  | 1500 | 0.3527          | 42.8105 |
| 0.2907        | 6.05  | 2000 | 0.3225          | 40.4267 |
| 0.2761        | 8.03  | 2500 | 0.3039          | 38.8974 |
| 0.2637        | 10.02 | 3000 | 0.2921          | 37.7927 |
| 0.2507        | 12.0  | 3500 | 0.2846          | 37.0733 |
| 0.2397        | 13.04 | 4000 | 0.2793          | 36.6004 |
| 0.243         | 15.03 | 4500 | 0.2763          | 36.3503 |
| 0.2501        | 17.01 | 5000 | 0.2754          | 36.2048 |


### Framework versions

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