---
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: 0.3426
- Wer: 78.6221

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- 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: 100
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4992        | 0.2075 | 100  | 0.4841          | 93.0091 |
| 0.4325        | 0.4149 | 200  | 0.4223          | 82.7761 |
| 0.4028        | 0.6224 | 300  | 0.3979          | 81.6616 |
| 0.3866        | 0.8299 | 400  | 0.3846          | 79.8886 |
| 0.3322        | 1.0373 | 500  | 0.3731          | 80.3951 |
| 0.3108        | 1.2448 | 600  | 0.3672          | 79.2300 |
| 0.3139        | 1.4523 | 700  | 0.3601          | 79.1287 |
| 0.324         | 1.6598 | 800  | 0.3558          | 78.7741 |
| 0.2629        | 1.8672 | 900  | 0.3525          | 78.1155 |
| 0.2421        | 2.0747 | 1000 | 0.3521          | 78.5208 |
| 0.217         | 2.2822 | 1100 | 0.3495          | 78.3688 |
| 0.2071        | 2.4896 | 1200 | 0.3490          | 78.5714 |
| 0.2183        | 2.6971 | 1300 | 0.3452          | 78.6727 |
| 0.2158        | 2.9046 | 1400 | 0.3426          | 78.6221 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3