---
language:
- hi
license: apache-2.0
base_model: arun100/whisper-base-hi-3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Hindi
  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: 27.6637932833796
---

<!-- 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 Base Hindi

This model is a fine-tuned version of [arun100/whisper-base-hi-3](https://huggingface.co/arun100/whisper-base-hi-3) on the mozilla-foundation/common_voice_16_0 hi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4681
- Wer: 27.6638

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1251        | 13.16 | 1000 | 0.4681          | 27.6638 |
| 0.0812        | 26.32 | 2000 | 0.5046          | 28.2065 |
| 0.0584        | 39.47 | 3000 | 0.5393          | 28.3046 |
| 0.0441        | 52.63 | 4000 | 0.5639          | 28.4924 |
| 0.0392        | 65.79 | 5000 | 0.5734          | 28.5863 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0