Update README.md

README.md

@@ -59,7 +59,7 @@ The augmentation simulates non-DESI instrument characteristics during training,
 | **SDSS (real non-DESI)** | 2000 | 0.382 | 0.385 | 0.127 |
 | **VIPERS (real non-DESI)** | 2000 | **0.172** | 0.087 | 0.274 (AION loses) |
 
-We beat AION-base on **DESI** by 30% and on **VIPERS** by 37%. SDSS is harder for our raw-flux architecture; for SDSS-style inputs, the AION-tokenizer-based variants in our ensemble are better.
+We beat AION-base on **DESI** by 30% and on **VIPERS** by 37%.
 
 ## Folder structure
 
@@ -67,24 +67,23 @@ We beat AION-base on **DESI** by 30% and on **VIPERS** by 37%. SDSS is harder fo
 NativeSpecZ-FM-76M_Submission/
 ├── NativeSpecZ-FM-76M.ipynb       ← demo notebook (load model, run eval, plot results)
 ├── README.md                       ← this file
-├── REPORT.md                       ← full methodology + results write-up
 ├── weights/
-│   ├── best.pt                     ← 292 MB model checkpoint
+│   ├── best.pt                     ← 306 MB model checkpoint
 │   ├── training_args.json          ← all hyperparameters
 │   └── best_metrics.json           ← training-time eval metrics
 ├── code/
-│   └── hybrid_redshift.py          ← model architecture + collator + training loop
+│   ├── hybrid_redshift.py          ← model architecture + collator + training loop
+│   ├── data.py, metrics.py, model.py, plots.py
 ├── eval_results/
-│   └── desi_2500_metrics.json      ← test-set metrics in friend-style format
+│   └── desi_2500_metrics.json
 └── plots/
-    ├── friend_style_scatter.png            ← Pearson r=0.9358 scatter (matches friend's format)
-    ├── friend_style_reconstruction.png     ← 4-panel masked recon overlay
-    ├── comparison_vs_aion.png              ← MAE bar chart vs AION-base
-    ├── comparison_3way_desi.png            ← 6-metric chart: us vs AION vs friend
-    ├── foundation_evidence.png             ← cross-instrument robustness ratio
-    ├── dashboard.png                       ← 6-panel model summary
-    ├── multi_mask_reconstruction.png       ← rec quality vs mask ratio
-    └── stress_curve.png                    ← instrument-shift robustness
+    ├── scatter_redshift.png        ← Predicted vs True scatter, Pearson r=0.9358
+    ├── spectrum_reconstruction.png ← 4-panel masked-region reconstruction overlay
+    ├── comparison_vs_aion.png      ← MAE bar chart vs AION-base
+    ├── foundation_evidence.png     ← cross-instrument robustness
+    ├── dashboard.png               ← 6-panel model summary
+    ├── multi_mask_reconstruction.png ← rec quality vs mask ratio
+    └── stress_curve.png            ← instrument-shift robustness
 ```
 
 ## How to reload the model
@@ -113,7 +112,7 @@ See `NativeSpecZ-FM-76M.ipynb` for the full inference + evaluation pipeline.
 
 ## Hugging Face
 
-Model also available at `tempAstro/NativeSpecZ-FM-76M` on Hugging Face.
+Model also available at `ManmohanSharma/NativeSpecZ-FM-76M` on Hugging Face.
 
 ## Submission checklist