---
language:
- hi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
  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: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 65.9189029035808
---

<!-- 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 Hi - Sanchit Gandhi

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: 0.5964
- Wer: 65.9189

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9954        | 0.02  | 10   | 2.0896          | 111.0937 |
| 1.4388        | 0.05  | 20   | 1.4497          | 106.8780 |
| 1.0201        | 0.07  | 30   | 0.9971          | 110.6281 |
| 0.7901        | 0.1   | 40   | 0.8241          | 80.4199  |
| 0.6572        | 0.12  | 50   | 0.7474          | 95.7039  |
| 0.6096        | 0.15  | 60   | 0.6896          | 85.3890  |
| 0.5228        | 0.17  | 70   | 0.6508          | 75.9672  |
| 0.5413        | 0.2   | 80   | 0.6219          | 67.5527  |
| 0.5319        | 0.22  | 90   | 0.6047          | 67.7516  |
| 0.4952        | 0.24  | 100  | 0.5964          | 65.9189  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2