Update model card with YAML front matter

README.md

@@ -1,32 +1,17 @@
+---
+tags:
+- addition
+- mathematics
+license: apache-2.0
+library_name: transformers
+accuracy_add: 0.99999
+train_loss: 8.6e-08
+---
 # QuantaMaths: `add_d15_l2_h3_t80K_s572091`
 
 This repository contains a transformer model that can predict addition questions.
 
 ### Model-specific metadata
 - **Operation type**: addition
-- **Num digits**: 15
-- **Layers**: 2
-- **Attention Heads**: 3
-- **Training steps**: 80,000
-- **Random seed**: 572091
-
-**Contents**:
-- `model.pth`: The trained transformer model.
-- `training_loss.json`: Data gathered during model training (used to plot "loss over training batches").
-- `behaviors.json`: Facts gathered about the model by direct inspection (attention pattern data, PCA data, digit impact data, etc.).
-- `features.json`: Facts gathered about hypothesized algorithm features via experimentation, e.g. node P12L0H1 implements the feature A3.ST.
-
-**Provenance**:
-- `model.pth` and `training_loss.json` were created by [QuantaMathsTrain.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsTrain.ipynb).
-- `behaviors.json` and `features.json` were created by [QuantaMathsAnalyse.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAnalyse.ipynb).
-- The JSON files are used by [QuantaMathsAlgorithm.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAlgorithm.ipynb).
-
-**Folder name details**:
-- "add", "sub", or "mix": The types of questions the model can predict.
-- "d5" to "d20": How many digits the model handles (e.g. a d5 sub model can predict the answer in 123450-345670=-0123230).
-- "l1", "l2", or "l3": The number of layers in the model.
-- "h3" or "h4": The number of attention heads in the model.
-- "t15K" to "t85K", etc.: The number of batches the model was trained on.
-- "s372001", etc.: The random seed used in model training.
-
 
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