---
library_name: transformers
language:
- zhc
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base zh-CN - fzuhyz
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: zhc
      split: test
      args: 'config: zhc, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 85.85000000000001
---

<!-- 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 zh-CN - fzuhyz

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5922
- Wer: 85.8500

## 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: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6972        | 0.8   | 1000 | 0.6448          | 88.8    |
| 0.5154        | 1.6   | 2000 | 0.6052          | 87.45   |
| 0.4207        | 2.4   | 3000 | 0.5945          | 86.3    |
| 0.353         | 3.2   | 4000 | 0.5935          | 85.45   |
| 0.3437        | 4.0   | 5000 | 0.5922          | 85.8500 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu118
- Datasets 2.16.0
- Tokenizers 0.21.1