---
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper large-v2 nan-tw only char
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 nan-tw
      type: mozilla-foundation/common_voice_11_0
      config: nan-tw
      split: test
      args: nan-tw
    metrics:
    - name: Wer
      type: wer
      value: 45.37404580152672
---

<!-- 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 only char

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: 1.0351
- Wer: 45.3740
- Cer: 45.4573

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.6011        | 1.04  | 1000 | 1.1100          | 55.0229 | 55.2068 |
| 0.1773        | 2.08  | 2000 | 1.2055          | 58.6565 | 58.7685 |
| 0.015         | 3.13  | 3000 | 1.0932          | 48.6412 | 48.8077 |
| 0.0131        | 5.01  | 4000 | 1.0531          | 45.7099 | 45.8497 |
| 0.0001        | 6.05  | 5000 | 1.0351          | 45.3740 | 45.4573 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2