Clip 336 LLama 3B Llava v3
This model is a fine-tuned version of []( on an unknown dataset.
Fuente del modelo
- Tipo
- Text model
- Tamaño del archivo
- 6,57 GB
- Versión
- vmodel
- Actualizado
- 24 oct 2026
- Publicador
- @MohamedAhmedAE
- Descargas
- 0
- Parámetros
- 3B
- Fuente
- Hugging Face
Descripción de la fuente
Clip_336_LLama_3B_llava_v3
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: 2e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- 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_with_min_lr
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
Training results
Framework versions
- Transformers 5.0.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 24 oct
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Artefactos del modelo
2 artefactos
Artefactos del modelo
2 artefactoslast-checkpoint/model.safetensors
safetensors · 6,57 GB · SHA-256 1af1e7ba7687…b4b1 · Hugging Face
Download fileExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- library_name: transformers tags: - generated_from_trainer model-index: - name: Clip_336_LLama_3B_llava_v3 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. --> # Clip_336_LLama_3B_llava_v3 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: 2e-05 - train_batch_size: 12 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 2 - total_train_batch_size: 24 - 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_with_min_lr - lr_scheduler_warmup_steps: 200 - num_epochs: 10 ### Training results ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 0 downloads · 0 likes · Library transformers · Repo MohamedAhmedAE/Clip_336_LLama_3B_llava_v3
Source context: 0 downloads · 1 likes · Library transformers · Repo MohamedAhmedAE/Clip_336_LLama_3B_llava_v3
