openfun-ivod-whisper-small-common-11-1200

Fine-tune 資訊

• 原始模型: openai/whisper-small
• 使用音訊數量: 202505
• 使用音訊總長: 122.56 小時
• 音訊平均長度: 2.18 秒
• GPU: NVIDIA H100 PCIe x 1
• 訓練時間: 04:02:06
• 模型大小: 0.90 GB
• 訓練參數:
  • batch size: 40
  • eval batch size: 20
  • gradient checkpointing: False
  • fp16: False
  • bf16: True

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Fine-tuned Whisper model for Legislative Yuan of Taiwan

This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0216
• Wer: 76.4284

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: 40
• eval_batch_size: 20
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 1000

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.5.1
• Datasets 3.5.0
• Tokenizers 0.21.1