Update README.md

README.md

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 license: cc-by-4.0
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+# # Synthetic mass spectra dataset No. 1
 This is the first variant of the GC-EI-MS synthetic dataset generated by NEIMS and RASSP models from 4.8 million structures downloaded from ZINC. 
-The overlap with version 2 is approximately 8k structures (negligible), so it's usable as an extension to synth2. 
+The overlap with version 2 is approximately 8k structures (negligible), so it's usable as an extension to synth2. If you're choosing between synth1
+and synth2, see section Dataset choice.
 
 For generating this dataset, we used the original NEIMS model downloaded from the official [NEIMS] repository. Since the [RASSP] model is not publicly available,
 we trained our own.
 
+## Dataset creation
+
+To uniformly cover the chemical space, we first scraped 1.8 billion SMILES strings from the ZINC20 library using the 2D-standard-annotated-druglike query. 
+From this dataset, we extracted a random sample of 30 million noncorrupted SMILES strings shorter than 100 characters. Further, we canonicalized, deduplicated,
+and stripped the SMILES of stereochemical information, as stereochemistry is not reliably translated into spectra and cannot be accurately detected.
+Additionally, we removed all NIST 20 compounds to prevent data leakage during the testing of our trained model in the future.
+
+To evaluate the impact of RASSP and NEIMS respective spectrum prediction capabilities on SpecTUS performance, we created two identical sets of spectra generated
+by each model. RASSP's strict input filters reduced the dataset to approximately 4.8 million compounds. In total, the pretraining datasets comprises 4.8 million
+unique compounds and 9.6 million unique spectra.
+
+Lastly, we split each synthetic dataset into training, validation, and test sets using a 0.9:0.05:0.05 ratio. The splitting process was random, but corresponding splits
+(training, validation, and test sets) for the NEIMS and RASSP-generated spectra contained the same compounds. Each training set contained 4.3 million spectra, while the
+validation and test sets each consisted of \numprint{240000} spectra.
+
+
 ## Dataset choice
 If you're choosing between synth1 and synth2 (and don't need both), choose synth2. Its origin is better documented, custom-NEIMS spectra are of better quality
 and the NIST train sets for training the NEIMS and RASSP models (that generated synth2) are identical. Plus we make the NIST splits available in our [GitHub repository] (#TODO))
 
 
+## Data format
+
+Each line of every file is a `json` comprising three items:
+
+```text
+{"intensity":[0.01,0.08,0.06,0.05 ... 0.02,0.79,0.34,0.12],
+"mz":[18,27,28,29,38,39,40,41,42,43, ... 202,203,270,271,272,299,300,301],
+"smiles":"CCC(C)C1CCCCN1C(=O)CNc1cccc(C#N)c1"}
+```
+
+
 [NEIMS]: https://github.com/brain-research/deep-molecular-massspec
 [RASSP]: https://github.com/thejonaslab/rassp-public
 [GitHub repository]: TODO