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doc: Update training plots with generalization gap and 7k iter metrics#40

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Eamon2009 merged 8 commits into
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v1.3.15
Jul 16, 2026
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doc: Update training plots with generalization gap and 7k iter metrics#40
Eamon2009 merged 8 commits into
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v1.3.15

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loss curves with an expanded 3-panel metrics suite
covering 7,000 iterations (~86 minutes of wall-clock time).

Changes include:

  • Extended iteration tracking showing continuous convergence down to
    a new best validation cross-entropy loss of 2.9971 at step 6800.
  • Added a dedicated 'Generalisation Gap (val - train)' panel to visualize
    overfitting/underfitting margins across training iterations, noting a
    final gap of 0.056.
  • Included explicit indicators for specific model checkpoint 'saved' states
    throughout the training run.

Added an image and updated the quick start section.
Introduce visual plots tracking cross-entropy loss over 6,000 steps
and ~78 minutes of wall-clock training time.

These curves serve as a baseline reference for the model's convergence
behavior. The plots highlight a steady decline in training loss down to
~3.4, while validation loss plateaus early on, achieving its best score
of 4.1319 at step 3900.

Adding these assets to the repository ensures we have a clear, permanent
record of this run's performance to compare against future optimization
and hyperparameter tuning passes.
* Update README with image and quick start section

Added an image and updated the quick start section.

* doc: Add training and validation loss curves to assets (#35)

* Update README with image and quick start section (#34)

Added an image and updated the quick start section.

* doc: Add training and validation loss curves to assets

Introduce visual plots tracking cross-entropy loss over 6,000 steps
and ~78 minutes of wall-clock training time.

These curves serve as a baseline reference for the model's convergence
behavior. The plots highlight a steady decline in training loss down to
~3.4, while validation loss plateaus early on, achieving its best score
of 4.1319 at step 3900.

Adding these assets to the repository ensures we have a clear, permanent
record of this run's performance to compare against future optimization
and hyperparameter tuning passes.

* main: Configure GPT-style model hyperparameters and tokenizer (#36)

* Update README with image and quick start section (#34)

Added an image and updated the quick start section.

* doc: Add training and validation loss curves to assets

Introduce visual plots tracking cross-entropy loss over 6,000 steps
and ~78 minutes of wall-clock training time.

These curves serve as a baseline reference for the model's convergence
behavior. The plots highlight a steady decline in training loss down to
~3.4, while validation loss plateaus early on, achieving its best score
of 4.1319 at step 3900.

Adding these assets to the repository ensures we have a clear, permanent
record of this run's performance to compare against future optimization
and hyperparameter tuning passes.

* main: Config model hyperparameters and tokenizer

* V1.3.15 (#37)

* Update README with image and quick start section (#34)

Added an image and updated the quick start section.

* doc: Add training and validation loss curves to assets

Introduce visual plots tracking cross-entropy loss over 6,000 steps
and ~78 minutes of wall-clock training time.

These curves serve as a baseline reference for the model's convergence
behavior. The plots highlight a steady decline in training loss down to
~3.4, while validation loss plateaus early on, achieving its best score
of 4.1319 at step 3900.

Adding these assets to the repository ensures we have a clear, permanent
record of this run's performance to compare against future optimization
and hyperparameter tuning passes.

* main: Config model hyperparameters and tokenizer

* Delete quadtrix_training_report.png

* Delete run.md
@Eamon2009 Eamon2009 merged commit 3bb8b6c into master Jul 16, 2026
2 of 3 checks passed
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