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Download multi_student_5/README.md from MultimodalAgent/PlanPhys-Model-Pre-Training-Distribution: direct link, hf CLI and curl.
- Browser
- Download file 1.31 kB
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https://huggingface.co/MultimodalAgent/PlanPhys-Model-Pre-Training-Distribution/resolve/91bc997ebbdcb868e3ef53cedef775da75ae6708/multi_student_5/README.md
- Command line
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hf download hf://MultimodalAgent/PlanPhys-Model-Pre-Training-Distribution@91bc997ebbdcb868e3ef53cedef775da75ae6708/multi_student_5/README.md
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curl -L -o README.md https://huggingface.co/MultimodalAgent/PlanPhys-Model-Pre-Training-Distribution/resolve/91bc997ebbdcb868e3ef53cedef775da75ae6708/multi_student_5/README.md
1.31 kB
multi_student_5
This model is a fine-tuned version of /data/mentianyi/code/PlanPhys/model_configs/qwen2_100M_paper_2_random_pretraining on the multi_student_5 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 7.0
Training results
Framework versions
- Transformers 4.57.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.22.2