---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
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: 0.3717
- Cer: 15.8574

## 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 | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5054        | 0.25  | 100  | 0.4976          | 21.1112 |
| 0.4526        | 0.5   | 200  | 0.4336          | 18.1724 |
| 0.4131        | 0.75  | 300  | 0.4105          | 20.9577 |
| 0.3772        | 1.0   | 400  | 0.3952          | 17.7166 |
| 0.297         | 1.25  | 500  | 0.3872          | 17.8054 |
| 0.2837        | 1.5   | 600  | 0.3798          | 18.3740 |
| 0.2801        | 1.75  | 700  | 0.3747          | 15.5887 |
| 0.2776        | 2.0   | 800  | 0.3677          | 16.4739 |
| 0.1981        | 2.25  | 900  | 0.3697          | 17.1169 |
| 0.2198        | 2.5   | 1000 | 0.3662          | 16.7474 |
| 0.2133        | 2.75  | 1100 | 0.3624          | 15.8334 |
| 0.2015        | 3.0   | 1200 | 0.3597          | 15.9798 |
| 0.1597        | 3.25  | 1300 | 0.3633          | 15.7902 |
| 0.1796        | 3.5   | 1400 | 0.3611          | 16.7834 |
| 0.145         | 3.75  | 1500 | 0.3607          | 16.6947 |
| 0.1581        | 4.0   | 1600 | 0.3602          | 16.2005 |
| 0.1235        | 4.25  | 1700 | 0.3639          | 14.9530 |
| 0.1118        | 4.5   | 1800 | 0.3674          | 15.3344 |
| 0.1266        | 4.75  | 1900 | 0.3654          | 15.3728 |
| 0.1214        | 5.0   | 2000 | 0.3644          | 15.3248 |
| 0.0911        | 5.25  | 2100 | 0.3678          | 15.8238 |
| 0.0969        | 5.5   | 2200 | 0.3703          | 15.8046 |
| 0.0956        | 5.75  | 2300 | 0.3717          | 15.8574 |


### Framework versions

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