---
language:
- zh
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper large zh - seiching
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: zh-TW
      split: test
      args: zh-TW
    metrics:
    - name: Wer
      type: wer
      value: 39.92812936713915
---

<!-- 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 zh - seiching

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2457
- Wer Ortho: 40.3316
- Wer: 39.9281

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.0361        | 0.69  | 500  | 0.1989          | 38.3627   | 37.9517 |
| 0.0105        | 1.38  | 1000 | 0.2217          | 39.0259   | 38.9100 |
| 0.0208        | 2.06  | 1500 | 0.2299          | 39.6891   | 39.3292 |
| 0.0091        | 2.75  | 2000 | 0.2264          | 39.8964   | 39.4091 |
| 0.0153        | 3.44  | 2500 | 0.2363          | 39.8135   | 39.3891 |
| 0.0191        | 4.13  | 3000 | 0.2415          | 40.1865   | 40.0080 |
| 0.0061        | 4.81  | 3500 | 0.2542          | 41.1813   | 39.9281 |
| 0.0107        | 5.5   | 4000 | 0.2457          | 40.3316   | 39.9281 |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.13.1+cu117
- Datasets 2.13.2
- Tokenizers 0.13.3