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---
language:
- zh
license: apache-2.0
base_model: xmzhu/whisper-tiny-zh
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Chinese-Mandarin
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 zh-CN
type: mozilla-foundation/common_voice_16_0
config: zh-CN
split: test
args: zh-CN
metrics:
- name: Wer
type: wer
value: 91.12657677250978
---
<!-- 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 Chinese-Mandarin
This model is a fine-tuned version of [xmzhu/whisper-tiny-zh](https://huggingface.co/xmzhu/whisper-tiny-zh) on the mozilla-foundation/common_voice_16_0 zh-CN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5759
- Wer: 91.1266
## 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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6689 | 0.2 | 200 | 0.5854 | 91.6311 |
| 0.6314 | 1.07 | 400 | 0.5791 | 91.1788 |
| 0.653 | 1.27 | 600 | 0.5759 | 91.1266 |
| 0.699 | 2.13 | 800 | 0.5749 | 91.2049 |
| 0.5613 | 3.0 | 1000 | 0.5744 | 91.1527 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
|