---
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper large-v2 nan-tw
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 nan-tw
      type: mozilla-foundation/common_voice_11_0
      config: nan-tw
      split: train
      args: nan-tw
    metrics:
    - type: wer
      value: 42.592995431803345
      name: Wer
    - type: cer
      value: 23.297031817211188
      name: Cer
---

<!-- 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 large-v2 nan-tw

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 nan-tw dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7525
- Wer: 42.5930
- Cer: 23.2970

## 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: 2
- eval_batch_size: 2
- 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     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.4781        | 1.04  | 1000 | 0.7256          | 52.4690 | 28.7583 |
| 0.1881        | 2.08  | 2000 | 0.7346          | 50.2067 | 26.6389 |
| 0.0429        | 3.13  | 3000 | 0.7094          | 45.3557 | 24.7811 |
| 0.0112        | 5.01  | 4000 | 0.7416          | 44.4203 | 24.6850 |
| 0.0011        | 6.05  | 5000 | 0.7525          | 42.5930 | 23.2970 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2