# QuantaMaths: `mix_d6_l3_h4_t40K_s372001`

### Model-specific metadata for `mix_d6_l3_h4_t40K_s372001`

- **Operation type**: mix
- **Max digits**: d6
- **Layers**: l3
- **Attention Heads**: h4
- **Training steps**: t40K
- **Random seed**: s372001

This repository contains a transformer model that can predict addition questions, subtraction questions, or both.

**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.

Some folder names also contain:
- "ins1": Before training, the model was initialized with a smaller, accurate addition model.
- "ins2": Same as ins1, but the inserted attention heads were not allowed to change.
- "ins3": Same as ins2, but the inserted MLP layers were also not allowed to change.

**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).