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kingabzpro/wav2vec2-60-Urdu-V8

🤗 Hugging Face 来源automatic-speech-recognitionapache-2.094M 参数378 MBsafetensors✓ 5 个校验和今天更新
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在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对，然后提交。你只需开始做种，并粘贴你账户中的密钥。它只读取你的文件，绝不修改。如果愿意，可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo kingabzpro/wav2vec2-60-Urdu-V8 ./model-folder
需要做种者 →

🔴Check out my latest URDU ASR model with 25 WER here -> kingabzpro/whisper-large-v3-turbo-urdu

wav2vec2-60-Urdu-V8

This model is a fine-tuned version of Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 11.4832
  • Wer: 0.5729
  • Cer: 0.3170

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 7.5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
19.671 8.33 100 7.7671 0.8795 0.4492
2.085 16.67 200 9.2759 0.6201 0.3320
0.6633 25.0 300 8.7025 0.5738 0.3104
0.388 33.33 400 10.2286 0.5852 0.3128
0.2822 41.67 500 11.1953 0.5738 0.3174
0.2293 50.0 600 11.4832 0.5729 0.3170

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.11.0