---
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large-v2 Hindi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 hi
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 11.303909898360956
---

<!-- 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-v2 Hindi

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 hi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3191
- Wer: 11.3039

## 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
- 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: 50
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0479        | 2.06  | 200  | 0.2189          | 12.3226 |
| 0.0081        | 5.06  | 400  | 0.2649          | 11.5740 |
| 0.001         | 8.06  | 600  | 0.2998          | 11.4252 |
| 0.0004        | 11.05 | 800  | 0.3191          | 11.3039 |
| 0.0003        | 14.05 | 1000 | 0.3267          | 11.3291 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2