PhilipQuirke commited on
Commit
1c07482
·
verified ·
1 Parent(s): bf03366

Update model card with YAML front matter

Browse files
Files changed (1) hide show
  1. README.md +31 -1
README.md CHANGED
@@ -14,4 +14,34 @@ This repository contains a transformer model that can predict subtraction questi
14
  ### Model-specific metadata
15
  - **Operation type**: subtraction
16
 
17
- (Your shared text, minus YAML, goes here...)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
  ### Model-specific metadata
15
  - **Operation type**: subtraction
16
 
17
+ # QuantaMaths: `sub_d10_l2_h3_t75K_gf_s173289`
18
+
19
+ This repository contains a transformer model that can predict subtraction questions.
20
+
21
+ ### Model-specific metadata
22
+ - **Operation type**: subtraction
23
+ - **Num digits**: 10
24
+ - **Layers**: 2
25
+ - **Attention Heads**: 3
26
+ - **Training steps**: 75,000
27
+
28
+ **Contents**:
29
+ - `model.pth`: The trained transformer model.
30
+ - `training_loss.json`: Data gathered during model training (used to plot "loss over training batches").
31
+ - `behaviors.json`: Facts gathered about the model by direct inspection (attention pattern data, PCA data, digit impact data, etc.).
32
+ - `features.json`: Facts gathered about hypothesized algorithm features via experimentation, e.g. node P12L0H1 implements the feature A3.ST.
33
+
34
+ **Provenance**:
35
+ - `model.pth` and `training_loss.json` were created by [QuantaMathsTrain.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsTrain.ipynb).
36
+ - `behaviors.json` and `features.json` were created by [QuantaMathsAnalyse.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAnalyse.ipynb).
37
+ - The JSON files are used by [QuantaMathsAlgorithm.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAlgorithm.ipynb).
38
+
39
+ **Folder name details**:
40
+ - "add", "sub", or "mix": The types of questions the model can predict.
41
+ - "d5" to "d20": How many digits the model handles (e.g. a d5 sub model can predict the answer in 123450-345670=-0123230).
42
+ - "l1", "l2", or "l3": The number of layers in the model.
43
+ - "h3" or "h4": The number of attention heads in the model.
44
+ - "t15K" to "t85K", etc.: The number of batches the model was trained on.
45
+ - "s372001", etc.: The random seed used in model training.
46
+
47
+