---
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hindi - Shripad Bhat
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 21.451908746990714
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: FLEURS
      type: google/fleurs
      config: hi_in
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 22.11
---

<!-- 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 Hindi - Shripad Bhat

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3909
- Wer: 21.4519

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4337        | 0.73  | 100  | 0.4874          | 47.5868 |
| 0.1894        | 1.47  | 200  | 0.3264          | 23.9482 |
| 0.1007        | 2.21  | 300  | 0.3101          | 22.5267 |
| 0.0984        | 2.94  | 400  | 0.3064          | 21.5723 |
| 0.0555        | 3.67  | 500  | 0.3325          | 22.0251 |
| 0.029         | 4.41  | 600  | 0.3439          | 21.4863 |
| 0.0163        | 5.15  | 700  | 0.3668          | 21.6468 |
| 0.0153        | 5.88  | 800  | 0.3756          | 21.4662 |
| 0.0081        | 6.62  | 900  | 0.3888          | 21.5035 |
| 0.0059        | 7.35  | 1000 | 0.3909          | 21.4519 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2