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Arithmetic Model L2 H4 D32

This model is a fine-tuned version of []( on an unknown dataset.

TipoOtherVersãoRevision 9c2d01fPublicador@CrossBaseArithmeticCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
137 KB
Versão
vRevision 9c2d01f
Atualizado
16 de out. de 2026
Downloads
15
Tarefas
Geração de texto
Fonte
Hugging Face

Descrição da fonte

arithmetic-model-L2_H4_D32

This model is a fine-tuned version of on an unknown 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: 128
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 0.05
  • num_epochs: 10

Training results

Framework versions

  • Transformers 5.12.0
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Fontes

1 fonte
Hugging FacePrimárioVersão 9c2d01fc4e287b789a44c296afbcc1a732be6eb1
huggingface.co/CrossBaseArithmetic/arithmetic-model-L2_H4_D32/tree/9c2d01fc4e287b789a44c296afbcc1a732be6eb1

Verificado 26 de set.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 137 KB · SHA-256 bd1bb0af9a95…1c2f · Hugging Face

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Trechos de fonte

3 trechos

--- library_name: transformers tags: - generated_from_trainer model-index: - name: arithmetic-model-L2_H4_D32 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. --> # arithmetic-model-L2_H4_D32 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown 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: 128 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 0.05 - num_epochs: 10 ### Training results ### Framework versions - Transformers 5.12.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 15 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo CrossBaseArithmetic/arithmetic-model-L2_H4_D32

Source context: 179 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo CrossBaseArithmetic/arithmetic-model-L2_H4_D32