---
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Custom Hi - Nikhil Bhargava
  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: 0.24870904935240837
---

<!-- 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 Custom Hi - Nikhil Bhargava

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 hi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3972
- Wer: 0.2487

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0282        | 4.89  | 1000 | 0.2700          | 0.2647 |
| 0.0025        | 9.78  | 2000 | 0.3434          | 0.2554 |
| 0.0001        | 14.67 | 3000 | 0.3640          | 0.2471 |
| 0.0           | 19.56 | 4000 | 0.3902          | 0.2494 |
| 0.0           | 24.45 | 5000 | 0.3972          | 0.2487 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3