transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer zh base_model:ZhihCheng/whisper-base-zh license:apache-2.0 endpoints_compatible region:us
---
language:
- zh
license: apache-2.0
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: 0.1986
- Wer: 68.75

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 0.0375        | 0.85  | 50   | 0.1724          | 68.75 |
| 0.0164        | 1.69  | 100  | 0.1800          | 68.75 |
| 0.0044        | 2.54  | 150  | 0.1788          | 68.75 |
| 0.0031        | 3.39  | 200  | 0.1927          | 68.75 |
| 0.0009        | 4.24  | 250  | 0.1736          | 62.5  |
| 0.0009        | 5.08  | 300  | 0.1984          | 75.0  |
| 0.0006        | 5.93  | 350  | 0.2019          | 75.0  |
| 0.0005        | 6.78  | 400  | 0.1988          | 75.0  |
| 0.0005        | 7.63  | 450  | 0.1989          | 68.75 |
| 0.0005        | 8.47  | 500  | 0.1986          | 68.75 |


### Framework versions

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