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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-large-zh-cv11
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: zh-CN
split: validation[:1000]
args: zh-CN
metrics:
- name: Wer
type: wer
value: 52.307692307692314
---
<!-- 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-large-zh-cv11
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2501
- Wer: 52.3077
- Cer: 8.9573
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.3314 | 0.83 | 1000 | 0.2110 | 65.7014 | 10.8047 |
| 0.2747 | 1.66 | 2000 | 0.2005 | 58.1900 | 9.4191 |
| 0.1989 | 2.49 | 3000 | 0.1983 | 56.1991 | 9.0939 |
| 0.1142 | 3.31 | 4000 | 0.2076 | 55.0226 | 9.1589 |
| 0.0747 | 4.14 | 5000 | 0.2131 | 56.3801 | 9.0483 |
| 0.0709 | 4.97 | 6000 | 0.2165 | 54.6606 | 8.9768 |
| 0.0432 | 5.8 | 7000 | 0.2222 | 54.0271 | 8.9508 |
| 0.0261 | 6.63 | 8000 | 0.2299 | 54.4796 | 9.0353 |
| 0.0152 | 7.46 | 9000 | 0.2290 | 52.7602 | 8.8076 |
| 0.0054 | 8.28 | 10000 | 0.2435 | 51.6742 | 8.5279 |
| 0.0028 | 9.11 | 11000 | 0.2421 | 53.0317 | 8.9833 |
| 0.0045 | 9.94 | 12000 | 0.2462 | 52.9412 | 8.7751 |
| 0.0016 | 10.77 | 13000 | 0.2501 | 52.3077 | 8.9573 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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