---
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-tiny
model-index:
- name: Whisper tiny Hindi
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: test
      args: hi
    metrics:
    - type: wer
      value: 41.54533990599564
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: FLEURS
      type: google/fleurs
      config: hi_in
      split: test
      args: hi
    metrics:
    - type: wer
      value: 41.63
      name: Wer
---

<!-- 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 tiny Hindi 

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5538
- Wer: 41.5453

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7718        | 0.73  | 100  | 0.8130          | 55.6890 |
| 0.5169        | 1.47  | 200  | 0.6515          | 48.2517 |
| 0.3986        | 2.21  | 300  | 0.6001          | 44.9931 |
| 0.3824        | 2.94  | 400  | 0.5720          | 43.5171 |
| 0.3328        | 3.67  | 500  | 0.5632          | 42.5112 |
| 0.2919        | 4.41  | 600  | 0.5594          | 42.7863 |
| 0.2654        | 5.15  | 700  | 0.5552          | 41.6428 |
| 0.2618        | 5.88  | 800  | 0.5530          | 41.8893 |
| 0.2442        | 6.62  | 900  | 0.5539          | 41.5740 |
| 0.238         | 7.35  | 1000 | 0.5538          | 41.5453 |


### Framework versions

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