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Hanhpt23
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whisper-tiny-chinesemed-v1

Automatic Speech Recognition
Transformers
Safetensors
Chinese
whisper
Generated from Trainer
Inference Endpoints
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whisper-tiny-chinesemed-v1 / README.md
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metadata
language:
  - zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: openai/whisper-tiny
    results: []

openai/whisper-tiny

This model is a fine-tuned version of openai/whisper-tiny on the Hanhpt23/ChineseMed dataset. It achieves the following results on the evaluation set:

  • Loss: 4.4161
  • Wer: 116.6667

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: 0.0001
  • train_batch_size: 8
  • 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: 100
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Wer
2.0985 1.0 371 2.8659 188.8889
1.6605 2.0 742 2.8279 102.2222
1.2794 3.0 1113 3.0839 110.0000
0.7344 4.0 1484 3.4284 107.7778
0.4201 5.0 1855 3.6794 142.2222
0.1934 6.0 2226 3.8480 111.1111
0.0892 7.0 2597 4.0445 112.2222
0.0609 8.0 2968 4.1135 107.7778
0.0421 9.0 3339 4.2117 116.6667
0.0264 10.0 3710 4.3500 118.8889
0.0168 11.0 4081 4.2340 110.0000
0.0098 12.0 4452 4.3287 115.5556
0.0053 13.0 4823 4.3447 111.1111
0.0012 14.0 5194 4.3370 118.8889
0.0031 15.0 5565 4.3509 118.8889
0.0012 16.0 5936 4.3898 115.5556
0.0003 17.0 6307 4.3852 115.5556
0.0002 18.0 6678 4.4175 116.6667
0.0002 19.0 7049 4.4100 116.6667
0.0002 20.0 7420 4.4161 116.6667

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1