metadata

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

zh-CN-1-model - whucedar

This model is a fine-tuned version of 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