---
language:
- zh
license: apache-2.0
base_model: xmzhu/whisper-tiny-zh
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Chinese-Mandarin
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 zh-CN
      type: mozilla-foundation/common_voice_16_0
      config: zh-CN
      split: test
      args: zh-CN
    metrics:
    - name: Wer
      type: wer
      value: 91.12657677250978
---

<!-- 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 Base Chinese-Mandarin

This model is a fine-tuned version of [xmzhu/whisper-tiny-zh](https://huggingface.co/xmzhu/whisper-tiny-zh) on the mozilla-foundation/common_voice_16_0 zh-CN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5759
- Wer: 91.1266

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6689        | 0.2   | 200  | 0.5854          | 91.6311 |
| 0.6314        | 1.07  | 400  | 0.5791          | 91.1788 |
| 0.653         | 1.27  | 600  | 0.5759          | 91.1266 |
| 0.699         | 2.13  | 800  | 0.5749          | 91.2049 |
| 0.5613        | 3.0   | 1000 | 0.5744          | 91.1527 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0