---
language:
- hi
license: apache-2.0
base_model: Aakali/whisper-medium-hi
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper medium-translate Hi - Aa
  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: 23.684210526315788
---

<!-- 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 medium-translate Hi - Aa

This model is a fine-tuned version of [Aakali/whisper-medium-hi](https://huggingface.co/Aakali/whisper-medium-hi) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4968
- Wer: 23.6842

## 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: 16
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0           | 1000.0 | 1000 | 1.2182          | 13.1579 |
| 0.0           | 2000.0 | 2000 | 1.7360          | 18.4211 |
| 0.0           | 3000.0 | 3000 | 2.1484          | 23.6842 |
| 0.0           | 4000.0 | 4000 | 2.5106          | 26.3158 |
| 0.0           | 5000.0 | 5000 | 2.4968          | 23.6842 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1