---
language:
- hi
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Hindi - base
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 hi
      type: mozilla-foundation/common_voice_16_0
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 28.50294181738941
---

<!-- 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. -->

# Breeze DSW Hindi - base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 hi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5205
- Wer: 28.5029

## 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: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.553         | 0.1   | 100  | 0.6445          | 39.4988 |
| 0.3683        | 1.08  | 200  | 0.5342          | 33.0660 |
| 0.2855        | 2.07  | 300  | 0.4983          | 31.4251 |
| 0.2233        | 3.06  | 400  | 0.4868          | 30.1547 |
| 0.1832        | 4.04  | 500  | 0.4783          | 28.9540 |
| 0.1431        | 5.03  | 600  | 0.4902          | 29.1828 |
| 0.0972        | 6.01  | 700  | 0.5049          | 28.6380 |
| 0.0715        | 6.11  | 800  | 0.5205          | 28.5029 |
| 0.0579        | 7.09  | 900  | 0.5366          | 28.9475 |
| 0.0519        | 8.08  | 1000 | 0.5381          | 28.7949 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0