---
base_model: openai/whisper-large-v3
datasets:
- google/fleurs
language:
- hi
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Large-v3 Hindi -megha sharma
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Google Fleurs
      type: google/fleurs
      config: hi_in
      split: None
      args: 'config: hi, split: test'
    metrics:
    - type: wer
      value: 18.4303006638032
      name: Wer
---

<!-- 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 Large-v3 Hindi -megha sharma

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1607
- Wer: 18.4303

## 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: 5e-06
- train_batch_size: 8
- 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: 2000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.1781        | 6.7797  | 2000  | 0.1785          | 21.1734 |
| 0.1519        | 13.5593 | 4000  | 0.1621          | 19.2405 |
| 0.1286        | 20.3390 | 6000  | 0.1577          | 18.7427 |
| 0.1259        | 27.1186 | 8000  | 0.1564          | 18.2058 |
| 0.111         | 33.8983 | 10000 | 0.1568          | 17.9032 |
| 0.1067        | 40.6780 | 12000 | 0.1582          | 17.8153 |
| 0.1034        | 47.4576 | 14000 | 0.1591          | 18.8403 |
| 0.0995        | 54.2373 | 16000 | 0.1603          | 18.8598 |
| 0.0929        | 61.0169 | 18000 | 0.1607          | 18.4303 |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1