transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer zh base_model:ZhihCheng/whisper-base-zh endpoints_compatible region:us
---
language:
- zh
base_model: ZhihCheng/whisper-base-zh
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
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# Whisper base ZH

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: 0.2200
- Wer: 44.8955

## 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
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1704        | 0.27  | 1000 | 0.2787          | 51.6077 |
| 0.1479        | 0.54  | 2000 | 0.2480          | 48.4124 |
| 0.1145        | 0.81  | 3000 | 0.2289          | 46.1415 |
| 0.076         | 1.08  | 4000 | 0.2200          | 44.8955 |


### Framework versions

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