|
---
|
|
language:
|
|
- zh
|
|
license: apache-2.0
|
|
base_model: openai/whisper-small
|
|
tags:
|
|
- hf-asr-leaderboard
|
|
- generated_from_trainer
|
|
datasets:
|
|
- whucedar/retrain_jiaozhu
|
|
metrics:
|
|
- wer
|
|
model-index:
|
|
- name: zh-CN-1-model - whucedar
|
|
results:
|
|
- task:
|
|
name: Automatic Speech Recognition
|
|
type: automatic-speech-recognition
|
|
dataset:
|
|
name: zh-CN
|
|
type: whucedar/retrain_jiaozhu
|
|
config: default
|
|
split: None
|
|
args: 'config: zh, split: test'
|
|
metrics:
|
|
- name: Wer
|
|
type: wer
|
|
value: 90.0
|
|
---
|
|
|
|
<!-- 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. -->
|
|
|
|
# zh-CN-1-model - whucedar
|
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the zh-CN dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.0135
|
|
- Wer: 90.0
|
|
|
|
## 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: 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: 50
|
|
- training_steps: 200
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
|
|:-------------:|:-----:|:----:|:---------------:|:----:|
|
|
| 0.0001 | 20.0 | 100 | 0.0135 | 90.0 |
|
|
| 0.0001 | 40.0 | 200 | 0.0135 | 90.0 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.42.3
|
|
- Pytorch 2.3.1+cu118
|
|
- Datasets 2.20.0
|
|
- Tokenizers 0.19.1
|
|
|
