---
library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- 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
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 47.02479338842976
---

<!-- 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: 0.5644
- Wer: 47.0248

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1700
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5424        | 0.4854 | 100  | 0.6264          | 65.1653 |
| 0.4626        | 0.9709 | 200  | 0.5054          | 56.4463 |
| 0.2254        | 1.4563 | 300  | 0.4883          | 57.9752 |
| 0.1756        | 1.9417 | 400  | 0.4684          | 52.7273 |
| 0.0827        | 2.4272 | 500  | 0.4958          | 52.1901 |
| 0.0579        | 2.9126 | 600  | 0.4807          | 50.9091 |
| 0.0233        | 3.3981 | 700  | 0.5169          | 50.5372 |
| 0.0175        | 3.8835 | 800  | 0.5269          | 49.1736 |
| 0.0061        | 4.3689 | 900  | 0.5338          | 47.8099 |
| 0.007         | 4.8544 | 1000 | 0.5347          | 50.0    |
| 0.0021        | 5.3398 | 1100 | 0.5416          | 47.8926 |
| 0.0034        | 5.8252 | 1200 | 0.5490          | 49.2562 |
| 0.0014        | 6.3107 | 1300 | 0.5583          | 47.7686 |
| 0.0011        | 6.7961 | 1400 | 0.5583          | 47.0661 |
| 0.001         | 7.2816 | 1500 | 0.5605          | 46.9008 |
| 0.0008        | 7.7670 | 1600 | 0.5632          | 47.0248 |
| 0.0008        | 8.2524 | 1700 | 0.5644          | 47.0248 |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.7.1+cu118
- Datasets 4.0.0
- Tokenizers 0.21.2