luyotw/openfun-ivod-whisper-small-negotiation-10-125

Fine-tune 資訊

• 原始模型: openai/whisper-small
• 使用音訊數量: 75478
• 使用音訊總長: 42.33 小時
• 音訊平均長度: 2.02 秒
• GPU: NVIDIA H100 PCIe x 1
• 訓練時間: 01:31:25
• 模型大小: 0.90 GB
• 訓練參數:
  • batch size: 32
  • eval batch size: 16
  • 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: 0.0246
• Wer: 82.9641

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: 32
• eval_batch_size: 16
• 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: 125
• training_steps: 1250

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0284	0.1060	250	0.0274	85.1458
0.0308	0.2120	500	0.0260	84.2204
0.0208	0.3179	750	0.0253	83.7457
0.0265	0.4239	1000	0.0248	83.0504
0.0254	0.5299	1250	0.0246	82.9641

Framework versions

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