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Whisper Nagamese Adapter

This model is a fine-tuned version of openai/whisper-small on the None dataset.

TipoLoRAModelo baseopenai/whisper-smallVersãoFP32Publicador@kibozoiUnratednota

Fonte do modelo

Tipo
LoRA
Tamanho do arquivo
13,5 MB
Modelo base
openai/whisper-small
Versão
vFP32
Atualizado
1 de nov. de 2026
Publicador
@kibozoi
Downloads
11
Fonte
Hugging Face

Descrição da fonte

whisper-nagamese-adapter

This model is a fine-tuned version of openai/whisper-small on the None 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: 0.001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • 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
  • lr_scheduler_warmup_steps: 50
  • training_steps: 400
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • PEFT 0.19.1
  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 5.0.0
  • Tokenizers 0.22.2

Fontes

1 fonte
Hugging FacePrimárioVersão 844b66e58e3bc9b61abaad16dff5c6a8c404f22a
huggingface.co/kibozoi/whisper-nagamese-adapter/tree/844b66e58e3bc9b61abaad16dff5c6a8c404f22a

Verificado 1 de nov.

Download files

Repository files

File inventory only; completeness is unverified.

Artefatos de modelo

1 artefato

adapter_model.safetensors

safetensors · FP32 (tensor header) · 13,5 MB · SHA-256 8307b35dfc66…00b3 · Hugging Face

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Trechos de fonte

3 trechos

--- library_name: peft license: apache-2.0 base_model: openai/whisper-small tags: - base_model:adapter:openai/whisper-small - lora - transformers model-index: - name: whisper-nagamese-adapter 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. --> # whisper-nagamese-adapter This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None 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: 0.001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - 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 - lr_scheduler_warmup_steps: 50 - training_steps: 400 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.19.1 - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 5.0.0 - Tokenizers 0.22.2

Source context: 11 downloads · 0 likes · Library peft · Repo kibozoi/whisper-nagamese-adapter

Source context: 287 downloads · 0 likes · Library peft · Repo kibozoi/whisper-nagamese-adapter