README.md

---
language:
- zh
base_model: ZhihCheng/whisper-base-zh
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base zh v2
  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 v2

This model is a fine-tuned version of [ZhihCheng/whisper-base-zh](https://huggingface.co/ZhihCheng/whisper-base-zh) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1522
- Wer: 75.0

## 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: 4
- eval_batch_size: 8
- 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 0.241         | 0.35  | 50   | 0.4000          | 75.0  |
| 0.1766        | 0.71  | 100  | 0.3001          | 75.0  |
| 0.1085        | 1.06  | 150  | 0.2594          | 81.25 |
| 0.059         | 1.42  | 200  | 0.2162          | 81.25 |
| 0.0412        | 1.77  | 250  | 0.1789          | 87.5  |
| 0.0347        | 2.13  | 300  | 0.1431          | 68.75 |
| 0.0172        | 2.48  | 350  | 0.1408          | 68.75 |
| 0.0137        | 2.84  | 400  | 0.1408          | 68.75 |
| 0.0081        | 3.19  | 450  | 0.1458          | 75.0  |
| 0.0074        | 3.55  | 500  | 0.1522          | 75.0  |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0a0+6a974be
- Datasets 2.16.1
- Tokenizers 0.15.1