v47 v29 Clean World Guard Lr35e7 Ep035
This model is a fine-tuned version of lldois/v29v19userworldguardlr8e7ep018 on the expv47cleanworldguard dataset.
Model source
- Kind
- Text model
- File size
- 1.49 GB
- Base model
- lldois/v29_v19_user_world_guard_lr8e7_ep018
- Version
- vmodel
- Updated
- Oct 22, 2026
- Downloads
- 16
- Source
- Hugging Face
Source description
v47_v29_clean_world_guard_lr35e7_ep035
This model is a fine-tuned version of lldois/v29_v19_user_world_guard_lr8e7_ep018 on the exp_v47_clean_world_guard 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: 3.5e-07
- train_batch_size: 1
- eval_batch_size: 8
- seed: 202607197
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 0.03
- num_epochs: 0.35
Training results
Framework versions
- Transformers 5.6.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Oct 22
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: other base_model: lldois/v29_v19_user_world_guard_lr8e7_ep018 tags: - llama-factory - full - generated_from_trainer model-index: - name: v47_v29_clean_world_guard_lr35e7_ep035 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. --> # v47_v29_clean_world_guard_lr35e7_ep035 This model is a fine-tuned version of [lldois/v29_v19_user_world_guard_lr8e7_ep018](https://huggingface.co/lldois/v29_v19_user_world_guard_lr8e7_ep018) on the exp_v47_clean_world_guard 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: 3.5e-07 - train_batch_size: 1 - eval_batch_size: 8 - seed: 202607197 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - 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: 0.03 - num_epochs: 0.35 ### Training results ### Framework versions - Transformers 5.6.0 - Pytorch 2.7.1+cu126 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 16 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo lldois/v47_v29_clean_world_guard_lr35e7_ep035
Source context: 271 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo lldois/v47_v29_clean_world_guard_lr35e7_ep035
