---
language:
- hi
license: apache-2.0
base_model: arun100/whisper-small-derived-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 hi
      type: mozilla-foundation/common_voice_16_0
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 9.288054935192335
---

<!-- 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-small-derived-hi-1](https://huggingface.co/arun100/whisper-small-derived-hi-1) on the mozilla-foundation/common_voice_16_0 hi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1458
- Wer: 9.2881

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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: 20
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1368        | 1.02  | 100  | 0.1665          | 9.6951 |
| 0.1196        | 2.05  | 200  | 0.1586          | 9.6011 |
| 0.107         | 3.07  | 300  | 0.1538          | 9.4008 |
| 0.1051        | 5.02  | 400  | 0.1504          | 9.3235 |
| 0.0988        | 6.05  | 500  | 0.1486          | 9.4467 |
| 0.0939        | 7.07  | 600  | 0.1474          | 9.4425 |
| 0.0901        | 9.02  | 700  | 0.1464          | 9.3006 |
| 0.0859        | 10.04 | 800  | 0.1459          | 9.4362 |
| 0.0859        | 11.07 | 900  | 0.1458          | 9.2881 |
| 0.0839        | 13.02 | 1000 | 0.1456          | 9.2901 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0