---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-zh
  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-base-zh

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4316
- Wer: 85.1032

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5085        | 0.2070 | 100  | 0.4641          | 89.6326 |
| 0.4047        | 0.4141 | 200  | 0.4315          | 88.2235 |
| 0.4156        | 0.6211 | 300  | 0.4055          | 86.8646 |
| 0.3826        | 0.8282 | 400  | 0.3907          | 87.2169 |
| 0.3087        | 1.0352 | 500  | 0.3806          | 86.9149 |
| 0.2709        | 1.2422 | 600  | 0.3775          | 87.0659 |
| 0.2707        | 1.4493 | 700  | 0.3681          | 85.7071 |
| 0.273         | 1.6563 | 800  | 0.3633          | 85.5561 |
| 0.2638        | 1.8634 | 900  | 0.3592          | 85.4051 |
| 0.1698        | 2.0704 | 1000 | 0.3613          | 85.6568 |
| 0.1849        | 2.2774 | 1100 | 0.3628          | 85.7574 |
| 0.1819        | 2.4845 | 1200 | 0.3645          | 85.4555 |
| 0.1712        | 2.6915 | 1300 | 0.3611          | 84.8515 |
| 0.1768        | 2.8986 | 1400 | 0.3573          | 84.3986 |
| 0.1265        | 3.1056 | 1500 | 0.3640          | 85.2038 |
| 0.1275        | 3.3126 | 1600 | 0.3661          | 85.4051 |
| 0.1277        | 3.5197 | 1700 | 0.3698          | 84.3986 |
| 0.1195        | 3.7267 | 1800 | 0.3684          | 85.3045 |
| 0.1176        | 3.9337 | 1900 | 0.3668          | 84.9522 |
| 0.0843        | 4.1408 | 2000 | 0.3764          | 84.9522 |
| 0.077         | 4.3478 | 2100 | 0.3801          | 84.8012 |
| 0.0853        | 4.5549 | 2200 | 0.3804          | 85.4051 |
| 0.0826        | 4.7619 | 2300 | 0.3827          | 84.8515 |
| 0.0759        | 4.9689 | 2400 | 0.3803          | 84.9522 |
| 0.0519        | 5.1760 | 2500 | 0.3959          | 84.9522 |
| 0.0578        | 5.3830 | 2600 | 0.3946          | 85.0528 |
| 0.0594        | 5.5901 | 2700 | 0.3956          | 85.0528 |
| 0.0598        | 5.7971 | 2800 | 0.3971          | 85.1535 |
| 0.0519        | 6.0041 | 2900 | 0.3980          | 84.7509 |
| 0.0421        | 6.2112 | 3000 | 0.4103          | 85.5058 |
| 0.0379        | 6.4182 | 3100 | 0.4124          | 84.9019 |
| 0.0363        | 6.6253 | 3200 | 0.4131          | 84.9019 |
| 0.0377        | 6.8323 | 3300 | 0.4149          | 85.2038 |
| 0.0286        | 7.0393 | 3400 | 0.4205          | 84.8515 |
| 0.0263        | 7.2464 | 3500 | 0.4257          | 84.6502 |
| 0.0309        | 7.4534 | 3600 | 0.4276          | 85.3548 |
| 0.0295        | 7.6605 | 3700 | 0.4282          | 85.3045 |
| 0.0266        | 7.8675 | 3800 | 0.4291          | 85.2038 |
| 0.0241        | 8.0745 | 3900 | 0.4308          | 85.1535 |
| 0.025         | 8.2816 | 4000 | 0.4316          | 85.1032 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1