Vumichien
Rank:Average Model Cost: $0.0000
Number of Runs: 3,504
Models by this creator
whisper-medium-jp
whisper-medium-jp
openai/whisper-medium This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set: Loss: 0.3029 Wer: 9.0355 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: linear lr_scheduler_warmup_steps: 500 training_steps: 5000 mixed_precision_training: Native AMP Training results Framework versions Transformers 4.26.0.dev0 Pytorch 1.13.0+cu117 Datasets 2.7.1.dev0 Tokenizers 0.13.2
$-/run
2.7K
Huggingface
whisper-large-v2-jp
whisper-large-v2-jp
openai/whisper-large-v2 This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set: Loss: 0.2352 Wer: 8.1166 Cer: 5.0032 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: 8 eval_batch_size: 8 seed: 42 gradient_accumulation_steps: 2 total_train_batch_size: 16 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: linear lr_scheduler_warmup_steps: 500 training_steps: 10000 mixed_precision_training: Native AMP Training results Framework versions Transformers 4.26.0.dev0 Pytorch 1.13.0+cu117 Datasets 2.7.1.dev0 Tokenizers 0.13.2
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157
Huggingface
whisper-large-v2-mix-jp
$-/run
148
Huggingface
emo-mobilebert
$-/run
122
Huggingface
albert-base-v2-imdb
$-/run
102
Huggingface
wav2vec2-large-xlsr-japanese
wav2vec2-large-xlsr-japanese
Platform did not provide a description for this model.
$-/run
70
Huggingface
tiny-albert
tiny-albert
tiny-albert This model is a fine-tuned version of hf-internal-testing/tiny-albert on an unknown dataset. It achieves the following results on the evaluation set: 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: optimizer: None training_precision: float32 Training results Framework versions Transformers 4.18.0 TensorFlow 2.8.0 Tokenizers 0.12.1
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49
Huggingface
albert-base-v2-squad2
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44
Huggingface
mobilebert-uncased-squad-v2
mobilebert-uncased-squad-v2
tf-mobilebert-uncased-squad-v2 This model is a fine-tuned version of csarron/mobilebert-uncased-squad-v2 on an unknown dataset. It achieves the following results on the evaluation set: 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: optimizer: None training_precision: float32 Training results Framework versions Transformers 4.17.0 TensorFlow 2.8.0 Tokenizers 0.11.6
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33
Huggingface
trillsson3-ft-keyword-spotting-13
trillsson3-ft-keyword-spotting-13
trillsson3-ft-keyword-spotting-13 This model is a fine-tuned version of vumichien/nonsemantic-speech-trillsson3 on the superb dataset. It achieves the following results on the evaluation set: Loss: 0.3093 Accuracy: 0.9153 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: 0.0003 train_batch_size: 16 eval_batch_size: 32 seed: 0 gradient_accumulation_steps: 4 total_train_batch_size: 64 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: linear lr_scheduler_warmup_ratio: 0.1 num_epochs: 20.0 mixed_precision_training: Native AMP Training results Framework versions Transformers 4.23.0.dev0 Pytorch 1.12.1+cu113 Datasets 2.6.1 Tokenizers 0.13.1
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32
Huggingface