README.md

metadata

language:
  - zh
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - thomas0104/nan_tw_soap_opera
metrics:
  - wer
base_model: openai/whisper-large-v2
model-index:
  - name: openai/whisper-large-v2
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: thomas0104/nan_tw_soap_opera nan-tw
          type: thomas0104/nan_tw_soap_opera
          config: nan-tw
          split: test
        metrics:
          - type: cer
            value: 63.42
            name: Cer

openai/large_v2_nan_tw_so_short_30s

This model is a fine-tuned version of openai/whisper-large-v2 on the thomas0104/nan_tw_soap_opera nan-tw dataset. It achieves the following results on the evaluation set:

• Loss: 1.3322
• Wer: 343.5629
• Cer: 63.42

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.1133	1.0	1000	1.3322	343.5629	416.4573

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.8.0
• Tokenizers 0.13.2