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Open-weight model

TSRDA

by Dhruv Jyoti Das Dhruv1000/TSRDA

TSRDA is an open-weight model from Dhruv Jyoti Das. Its published files total 1.4 GB.

is the previous three-component system plus a separately trained, small temporal CNN—not a new version of the spatial–temporal backbone. “Above” means the existing SAM-optimizer network + training-derived prototypes + original temporal CNN.

Parameters—
Context—
Weights1.4 GB
License—
AccessOpen weights
Monthly Downloads—

Model Card

is the previous three-component system plus a separately trained, small temporal CNN—not a new version of the spatial–temporal backbone. “Above” means the existing SAM-optimizer network + training-derived prototypes + original temporal CNN. The additional CNN uses the same labeled sample lists, fixed 32×32 crops and seed value 3407. We call it a control because we trained it alongside the attention-CNN and Transformer candidates to determine whether those architectural changes helped beyond simply training another model. For each spatial pixel it reads the sequence of ten Sentinel-2 spectral bands. Its convolutions operate along time, not across neighboring image pixels: It has 28,306…

Excerpt from the card by Dhruv Jyoti Das.

Identity and Version

Repository
Dhruv1000/TSRDA
Publisher
Dhruv Jyoti Das
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
33ca008b0c2357e66ba5f9b1d0fa4a38540ee47f
First published
2026-08-26
Last updated
2026-10-07

Files and Weights

468 files, 1.4 GB in total.

Configuration298 files · 7.0 MB
Documentation20 files · 365.2 KB
Other149 files · 1.4 GB
Repository1 file · 2.2 KB
Every file
FileTypeSizeSHA-256
check_data.pyConfiguration6.5 KB —
check_split.pyConfiguration3.2 KB —
checkpoints/finetune/32X32_EMA_consistency/metadata.jsonConfiguration499 B —
checkpoints/finetune/32X32_L2SP/metadata.jsonConfiguration493 B —
checkpoints/finetune/32X32_SAM_refinement/metadata.jsonConfiguration492 B —
checkpoints/finetune/32X32_SWA_trajectory/metadata.jsonConfiguration492 B —
checkpoints/finetune/32X32_cereal_seed1234/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_cereal_seed3407/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_cereal_seed42/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_class_queries_seed3407/metadata.jsonConfiguration392 B —
checkpoints/finetune/32X32_encoder_lr_0.1/metadata.jsonConfiguration510 B —
checkpoints/finetune/32X32_exp1_low_lr/history.jsonConfiguration7.9 KB —
checkpoints/finetune/32X32_exp2_no_temporal_aug/history.jsonConfiguration32.9 KB —
checkpoints/finetune/32X32_exp3_masked_ce/history.jsonConfiguration39.6 KB —
checkpoints/finetune/32X32_exp4_fast_ema/history.jsonConfiguration29.7 KB —
checkpoints/finetune/32X32_exp5_boundary_01/history.jsonConfiguration24.5 KB —
checkpoints/finetune/32X32_fixed_baseline/history.jsonConfiguration29.7 KB —
checkpoints/finetune/32X32_freeze3_encoder_lr_0.1/metadata.jsonConfiguration516 B —
checkpoints/finetune/32X32_fresh_original_seed3407/metadata.jsonConfiguration395 B —
checkpoints/finetune/32X32_full_seed1234/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_full_seed3407/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_full_seed42/metadata.jsonConfiguration6.3 KB —
checkpoints/finetune/32X32_inherited_SSL_pilot/metadata.jsonConfiguration395 B —
checkpoints/finetune/32X32_low_lr_refinement/metadata.jsonConfiguration517 B —
checkpoints/finetune/32X32_mask_control/metadata.jsonConfiguration394 B —
checkpoints/finetune/32X32_mask_corrected/metadata.jsonConfiguration394 B —
checkpoints/finetune/32X32_pixel_contrastive/metadata.jsonConfiguration495 B —
checkpoints/finetune/32X32_shared_pool_mask_seed3407/metadata.jsonConfiguration393 B —
checkpoints/finetune/32X32_structured_SSL_pilot/metadata.jsonConfiguration394 B —
checkpoints/finetune/32X32_temporal_blend_seed3407/manifest.jsonConfiguration697 B —
checkpoints/finetune/32X32_top5_contrast_matched_adamw/metadata.jsonConfiguration394 B —
checkpoints/finetune/32X32_top5_contrast_sam/metadata.jsonConfiguration501 B —
checkpoints/finetune/32X32_top5_mask_matched_adamw/metadata.jsonConfiguration394 B —
checkpoints/finetune/32X32_top5_sam_batch_stats/metadata.jsonConfiguration509 B —
checkpoints/finetune/32X32_top5_sam_matched_adamw/metadata.jsonConfiguration392 B —
checkpoints/finetune/32X32_top5_seasonal_matched_adamw/metadata.jsonConfiguration395 B —
checkpoints/finetune/32X32_top5_temporal_mask/metadata.jsonConfiguration505 B —
checkpoints/finetune/64X64_random_crops/history.jsonConfiguration17.8 KB —
checkpoints/finetune/metadata.jsonConfiguration1.2 KB —
config.pyConfiguration14.9 KB —
dataset.pyConfiguration7.1 KB —
evaluate.pyConfiguration9.1 KB —
evaluate_plateau.pyConfiguration9.5 KB —
evaluate_temporal_blend.pyConfiguration3.5 KB —
finetune.pyConfiguration33.0 KB —
finetune_plateau.pyConfiguration39.4 KB —
finetune_research.pyConfiguration35.5 KB —
finetune_top5.pyConfiguration38.8 KB —
losses.pyConfiguration3.0 KB —
model.pyConfiguration18.0 KB —
plateau_models.pyConfiguration5.6 KB —
plateau_probes.pyConfiguration18.8 KB —
preflight.pyConfiguration11.9 KB —
pretrain.pyConfiguration10.8 KB —
pretrain_structured_pilot.pyConfiguration5.5 KB —
reports/32X32_exp1_low_lr/history.jsonConfiguration7.9 KB —
reports/32X32_exp2_no_temporal_aug/history.jsonConfiguration32.9 KB —
reports/32X32_exp3_masked_ce/history.jsonConfiguration39.6 KB —
reports/32X32_exp3_masked_ce/test_results.jsonConfiguration8.8 KB —
reports/32X32_exp4_fast_ema/history.jsonConfiguration29.7 KB —
reports/32X32_exp5_boundary_01/history.jsonConfiguration24.5 KB —
reports/32X32_fixed_baseline/history.jsonConfiguration29.7 KB —
reports/64X64_random_crops/history.jsonConfiguration17.8 KB —
reports/final/ALL_EXPERIMENTS.jsonConfiguration17.1 KB —
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reports/final/raw/overnight_research/32X32_structured_pilot_finetune/history.jsonConfiguration43.4 KB —
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