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Wav2vec2 Ks

This model is a fine-tuned version of facebook/wav2vec2-base on the SUPERB Keyword Spotting dataset.

KindOtherBase modelfacebook/wav2vec2-baseVersionRevision 99ab759

Model source

Kind
Other
File size
361 MB
Base model
facebook/wav2vec2-base
Version
vRevision 99ab759
Updated
Sep 19, 2026
Downloads
9
Source
Hugging Face

Source description

wav2vec2-base-finetuned-ks

This model is a fine-tuned version of facebook/wav2vec2-base on the SUPERB Keyword Spotting dataset.

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: 0.0002
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: tpu
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • training_steps: 3000

Training results

Framework versions

  • Transformers 4.57.6
  • Pytorch 2.9.0+cpu
  • Datasets 4.5.0
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion 99ab759a47e9fc1a925ff050430a4d6980db4d9d
huggingface.co/explorer7/wav2vec2-ks/tree/99ab759a47e9fc1a925ff050430a4d6980db4d9d

Verified Sep 19

Model artifacts

1 artifact

model.safetensors

safetensors · 361 MB · SHA-256 26915ee36f05…7dc5 · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - superb/ks model-index: - name: wav2vec2-base-finetuned-ks results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wav2vec2-base-finetuned-ks This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the SUPERB Keyword Spotting dataset. ## 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: 0.0002 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - distributed_type: tpu - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - training_steps: 3000 ### Training results ### Framework versions - Transformers 4.57.6 - Pytorch 2.9.0+cpu - Datasets 4.5.0 - Tokenizers 0.22.2

Source context: 9 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo explorer7/wav2vec2-ks