Update README.md

README.md

@@ -4,4 +4,64 @@ language:
 - en
 base_model:
 - microsoft/Phi-4-multimodal-instruct
----
+---
+
+##Galactus
+This model is a fine-tuned version of microsoft/Phi-4-multimodal-instruct on the Galaxy's Last Exam Benchmark.
+
+Galaxy's Last Exam Benchmark: 72%
+
+##Model description
+Galactus is a state-of-the-art (SOTA) multimodal language model that outperforms all OpenAI and Gemini models on the Galaxy's Last Exam Benchmark. This benchmark features challenging tasks that push the boundaries of metaphysical competence—for instance, determining how many times two lines intersect or simulating the effect of adding three minutes to an analog clock.
+The model accepts image input along with text prompts and has been specifically optimized to tackle complex visual reasoning tasks.
+
+##Intended uses & limitations
+This model is intended for handling complex visual reasoning tasks that require metaphysical competence.
+
+##Training and evaluation data
+The model was exclusively trained on the Galaxy's Last Exam Benchmark.
+
+##Training procedure
+The model was trained using LoRA adapters focused on the vision components of the base model.
+
+##Prompt format
+This model uses the following image prompt format:
+Copy<|image_1|> + user text
+
+##Training hyperparameters
+The following hyperparameters were used during training:
+
+num_train_epochs: specified in args
+per_device_train_batch_size: specified in args
+gradient_checkpointing: True
+gradient_checkpointing_kwargs: {'use_reentrant': False}
+gradient_accumulation_steps: specified in args
+optim: 'adamw_torch'
+adam_beta1: 0.9
+adam_beta2: 0.95
+adam_epsilon: 1e-7
+learning_rate: specified in args
+weight_decay: 0.0 or as specified in args
+save_strategy: 'steps'
+save_steps: 10
+eval_steps: 10 if eval_dataset else None
+evaluation_strategy: 'steps' if eval_dataset else 'no'
+load_best_model_at_end: True if eval_dataset else False
+max_grad_norm: 1.0
+lr_scheduler_type: 'linear'
+warmup_steps: 50
+logging_steps: 10
+save_total_limit: 2
+save_only_model: True
+dataloader_num_workers: 4
+ddp_find_unused_parameters: True
+
+##Training results
+The model achieved 72% performance on the Galaxy's Last Exam Benchmark.
+
+##Framework versions
+
+Transformers 4.46.1
+PyTorch 2.7.0.dev20250304+cu128
+TorchVision 0.22.0.dev20250304+cu128
+Tokenizers 0.20.3