Gpt2 256D 3L 8H
This model is a fine-tuned version of []( on an unknown dataset.
Modellquelle
- Art
- Other
- Dateigröße
- 9,19 MB
- Version
- vRevision e6ddcb4
- Aktualisiert
- 22. Okt. 2026
- Verleger
- @arithmetic-circuit-overloading
- 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
Quellen
1 QuelleVerifiziert 22. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
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
