---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi gpu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: test
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 194.9420130364852
---

<!-- 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 Small Hi gpu

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8500
- Wer: 194.9420

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 8.6847        | 2.44  | 500  | 8.6186          | 184.5213 |
| 7.0074        | 4.88  | 1000 | 6.9394          | 502.2010 |
| 5.0316        | 7.32  | 1500 | 4.9749          | 693.9939 |
| 3.7844        | 9.76  | 2000 | 3.7445          | 447.2488 |
| 3.2504        | 12.2  | 2500 | 3.2245          | 326.1619 |
| 3.0134        | 14.63 | 3000 | 2.9979          | 217.9463 |
| 2.8995        | 17.07 | 3500 | 2.8893          | 213.6164 |
| 2.8678        | 19.51 | 4000 | 2.8500          | 194.9420 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+rocm5.4.2
- Datasets 2.14.5
- Tokenizers 0.12.1