| # Experiment general info | |
| name: "OV_MSQA" | |
| rng_seed: 42 | |
| num_gpu: 2 | |
| mode: "train" | |
| note: "" | |
| # Choose keywords to feature your saving directory | |
| naming_keywords: ["dataloader.batchsize", "task", "note", "time"] | |
| base_dir: "results" | |
| exp_dir: "" | |
| save_frequency: 100 | |
| resume: False | |
| debug: | |
| flag: False | |
| hard_debug: False | |
| debug_size: 20 | |
| logger: | |
| name: "wandb" | |
| entity: "yem" | |
| # dataset details | |
| data: | |
| train: ['ScanNetMSQA'] | |
| val: ['ScanNetMSQA'] | |
| test: ['ScanNetMSQA'] | |
| args: | |
| max_obj_len: 80 | |
| max_seq_len: 50 | |
| num_points: 1024 | |
| pc_type: 'pred' | |
| sem_type: '607' | |
| filter_lang: False | |
| rot_aug: True | |
| ScanNetMSQA: | |
| train: | |
| use_unanswer: True | |
| val: | |
| use_unanswer: True | |
| test: | |
| use_unanswer: True | |
| use_voxel: False | |
| scan_family_base: "PointMapVerse/existing_datasets/ScanNet" | |
| rscan_base: "PointMapVerse/existing_datasets/3RScan" | |
| # task details: 'pretrain', 'scanrefer', 'referit3d', 'scanqa', 'default' | |
| task: 'MSQA' | |
| data_wrapper: | |
| train: 'ScanFamilyDatasetWrapperQA' | |
| val: 'ScanFamilyDatasetWrapperQA' | |
| test: 'ScanFamilyDatasetWrapperQA' | |
| # Training details | |
| trainer: "DefaultTrainer" | |
| ckpt_path: "" | |
| pretrain_ckpt_path: "" | |
| # dataloader details | |
| dataloader: | |
| # This is a per-gpu batchsize | |
| batchsize: 32 | |
| num_workers: 2 | |
| balance_dataset: False | |
| filter_empty_annotations: False | |
| solver: | |
| gradient_accumulation_steps: 1 | |
| epochs_per_save: 20 | |
| epochs_per_eval: 1 | |
| lr: 1e-4 | |
| grad_norm: 5.0 | |
| epochs: 100 | |
| optim: | |
| name: "AdamW" | |
| args: | |
| betas: [0.9, 0.98] | |
| sched: | |
| name: "warmup_cosine" | |
| args: | |
| warmup_steps: 5000 | |
| eval: | |
| name: "MSQAEval" | |
| save: False | |
| # Model details | |
| model: | |
| name: OpenVocab | |
| language: | |
| # This part could be further optimized to be using | |
| # huggingface yaml config files | |
| name: "BERTLanguageEncoder" | |
| args: | |
| weights: "fg-clip-base" | |
| hidden_size: 768 | |
| num_hidden_layers: 4 | |
| num_attention_heads: 12 | |
| type_vocab_size: 2 | |
| lr: 1e-5 | |
| vision: | |
| # name: "pointnet_point_encoder" | |
| # args: | |
| # path: None | |
| # freeze: False | |
| name: 'fg-clip-base' | |
| args: | |
| backbone: "SigLIPLanguageEncoder" | |
| hidden_size: 768 | |
| freeze: True | |
| path: 'fg-clip-base' | |
| num_attention_heads: 12 | |
| spatial_dim: 5 | |
| num_layers: 4 | |
| dim_loc: 6 | |
| dim_feedforward: 2048 | |
| attn_type: spatial | |
| pairwise_rel_type: 'center' | |
| use_matmul_label: False | |
| lang_type: 'bert' | |
| lang_path: 'pretrained_weights/607_text_embeddings' | |
| lr: 1e-4 | |
| grounding: | |
| name: 'UnifiedSpatialCrossEncoderV2' | |
| args: | |
| hidden_size: 768 | |
| num_attention_heads: 12 | |
| num_layers: 4 | |
| dim_feedforward: 2048 | |
| dim_loc: 6 | |
| lr: 1e-4 | |
| inter: before | |
| heads: | |
| head_list: ["qa_head"] | |
| qa_head: | |
| name: "QAHeadV1" | |
| args: | |
| hidden_size: 768 | |
| mlp_size: 256 | |
| glimpse: 1 | |
| flat_out_size: 512 | |
| num_answers: 42654 | |
| loss_type: "ListLoss" | |
| loss_list: [ | |
| "answer_loss" | |
| ] | |
| vis_loss_list: [ | |
| "answer_loss" | |
| ] | |