luyotw/openfun-ivod-whisper-large-v3-KeZhiEn-11-55

Fine-tune 資訊

• 原始模型: openai/whisper-large-v3
• 使用音訊數量: 11813
• 使用音訊總長: 5.86 小時
• 音訊平均長度: 1.79 秒
• GPU: NVIDIA H100 PCIe x 1
• 訓練時間: 01:53:45
• 模型大小: 5.75 GB
• 訓練參數:
  • batch size: 80
  • eval batch size: 40
  • gradient checkpointing: True
  • 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-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0223
• Wer: 75.3301

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: 80
• eval_batch_size: 40
• 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: 50
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0219	0.6757	100	0.0216	75.3863
0.0147	1.3514	200	0.0212	74.3467
0.0136	2.0270	300	0.0208	74.8806
0.0118	2.7027	400	0.0217	74.9368
0.0093	3.3784	500	0.0223	75.3301

Framework versions

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