---
language:
- vi
base_model: openai/whisper-medium-ja-v2
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Vi - Anh Phuong
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ja
      split: None
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 62.82245827010622
---

<!-- 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 - Anh Phuong

This model is a fine-tuned version of [openai/whisper-medium-ja-v2](https://huggingface.co/openai/whisper-medium-ja-v2) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3098
- Wer: 62.8225

## 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: 4
- 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.1131        | 1.4556 | 1000 | 0.2257          | 68.5454 |
| 0.0579        | 2.9112 | 2000 | 0.2363          | 65.5105 |
| 0.0087        | 4.3668 | 3000 | 0.2685          | 65.1203 |
| 0.003         | 5.8224 | 4000 | 0.2924          | 63.9931 |
| 0.0007        | 7.2780 | 5000 | 0.3041          | 63.1043 |
| 0.0005        | 8.7336 | 6000 | 0.3098          | 62.8225 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1