---
language:
- vi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Vi v1 - Shiv Kumar Ganesh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: vi
      split: test
      args: vi
    metrics:
    - name: Wer
      type: wer
      value: 34.09738977846019
---

<!-- 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 Vi v1 - Shiv Kumar Ganesh

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: 1.0641
- Wer: 34.0974

## 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: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0005        | 31.0  | 500  | 0.7179          | 33.7464 |
| 0.0002        | 62.0  | 1000 | 0.7837          | 32.4742 |
| 0.0001        | 93.0  | 1500 | 0.8267          | 34.2729 |
| 0.0001        | 124.0 | 2000 | 0.8677          | 35.1722 |
| 0.0           | 156.0 | 2500 | 0.9045          | 35.3257 |
| 0.0           | 187.0 | 3000 | 0.9316          | 33.9877 |
| 0.0           | 218.0 | 3500 | 0.9585          | 34.0097 |
| 0.0           | 249.0 | 4000 | 0.9846          | 33.3626 |
| 0.0           | 281.0 | 4500 | 1.0082          | 33.4832 |
| 0.0           | 312.0 | 5000 | 1.0247          | 33.7026 |
| 0.0           | 343.0 | 5500 | 1.0391          | 32.8691 |
| 0.0           | 374.0 | 6000 | 1.0516          | 32.9020 |
| 0.0           | 406.0 | 6500 | 1.0606          | 33.6477 |
| 0.0           | 437.0 | 7000 | 1.0641          | 34.0974 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2