---
language:
- zh
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-tiny
datasets:
- mozilla-foundation/common_voice_16_1
model-index:
- name: Whisper Tiny chinese - VingeNie
  results: []
---

<!-- 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 Tiny chinese - VingeNie

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6244
- Cer Ortho: 28.9724
- Cer: 24.2287

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer Ortho | Cer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.783         | 0.4796 | 600  | 0.7962          | 54.2372   | 31.6835 |
| 0.6578        | 0.9592 | 1200 | 0.6968          | 32.3398   | 27.9872 |
| 0.5028        | 1.4388 | 1800 | 0.6624          | 40.8123   | 27.6832 |
| 0.4887        | 1.9185 | 2400 | 0.6265          | 31.8488   | 25.8712 |
| 0.3368        | 2.3981 | 3000 | 0.6200          | 31.5221   | 25.3234 |
| 0.3395        | 2.8777 | 3600 | 0.6106          | 38.9218   | 25.3534 |
| 0.2078        | 3.3573 | 4200 | 0.6184          | 28.7037   | 24.7440 |
| 0.1943        | 3.8369 | 4800 | 0.6139          | 32.2586   | 24.3287 |
| 0.1206        | 4.3165 | 5400 | 0.6272          | 30.4763   | 24.2656 |
| 0.102         | 4.7962 | 6000 | 0.6244          | 28.9724   | 24.2287 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1