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Gpt2 256D 3L 8H

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

ArtOtherVersionRevision e6ddcb4Verleger@arithmetic-circuit-overloadingCBewertung

Modellquelle

Art
Other
Dateigröße
9,19 MB
Version
vRevision e6ddcb4
Aktualisiert
22. Okt. 2026
Downloads
15
Quelle
Hugging Face

Quellenbeschreibung

gpt2-256D-3L-8H

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: 20

Training results

Framework versions

  • Transformers 5.12.0
  • Pytorch 2.9.1+cu128
  • Datasets 5.0.0
  • Tokenizers 0.22.2

Quellen

1 Quelle
Hugging FacePrimärVersion e6ddcb421a44e688b2f81cb79e111395a04e45c3
huggingface.co/arithmetic-circuit-overloading/gpt2-256D-3L-8H/tree/e6ddcb421a44e688b2f81cb79e111395a04e45c3

Verifiziert 22. Okt.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 9,19 MB · SHA-256 8b1fe0cd0528…0995 · Hugging Face

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Quellenauszüge

3 Auszüge

--- library_name: transformers tags: - generated_from_trainer model-index: - name: gpt2-256D-3L-8H 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. --> # gpt2-256D-3L-8H 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: 20 ### Training results ### Framework versions - Transformers 5.12.0 - Pytorch 2.9.1+cu128 - Datasets 5.0.0 - Tokenizers 0.22.2

Source context: 15 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo arithmetic-circuit-overloading/gpt2-256D-3L-8H

Source context: 110 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo arithmetic-circuit-overloading/gpt2-256D-3L-8H