---
library_name: transformers
language:
- he
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: 30.46731826511912
---

<!-- 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: 0.5304
- Wer: 30.4673

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.3345        | 1.7778  | 500  | 0.4103          | 43.8302 |
| 0.1379        | 3.5556  | 1000 | 0.4276          | 37.6756 |
| 0.0612        | 5.3333  | 1500 | 0.4672          | 32.8039 |
| 0.0234        | 7.1111  | 2000 | 0.4806          | 32.9948 |
| 0.0167        | 8.8889  | 2500 | 0.4829          | 31.0247 |
| 0.0074        | 10.6667 | 3000 | 0.5092          | 34.4762 |
| 0.0023        | 12.4444 | 3500 | 0.5247          | 29.9786 |
| 0.0008        | 14.2222 | 4000 | 0.5304          | 30.4673 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1