Aesop-RL Model Checkpoint

This repository contains trained model weights for the Aesop-RL project.

Model Details

  • Model Type: Policy Network for Aesop Configuration
  • Training Stage: warm_up
  • Framework: PyTorch
  • Lean Version: 4

Architecture Validation

Not validated

Validation Results

Not run

Files

  • best_gen13.pt: PyTorch checkpoint (1083.0 MB)

Usage

import torch
from aesop.models.policy import AesopPolicy

# Load checkpoint
checkpoint = torch.load("warm_up_best.pt", map_location="cpu")
model = AesopPolicy()
model.load_state_dict(checkpoint['model_state_dict'])

Training Info

{
  "stage": "warm_up",
  "keys": [
    "epoch",
    "global_step",
    "best_val_acc",
    "model_state_dict",
    "wandb_run_id",
    "random_seed",
    "random_state",
    "numpy_random_state",
    "torch_rng_state",
    "global_moving_avg",
    "global_moving_std",
    "optimizer_0_state_dict",
    "optimizer_1_state_dict",
    "optimizer_2_state_dict",
    "cuda_rng_state",
    "scaler_state_dict",
    "trainer_state_dict",
    "metrics"
  ],
  "epoch": 3,
  "best_val_acc": 0.27459016393442626,
  "model_architecture": {
    "is_valid": true,
    "components": [
      {
        "name": "shared_mlp",
        "found_keys": 3,
        "total_expected": 3
      },
      {
        "name": "tactic_heads",
        "found_keys": 2,
        "total_expected": 2
      },
      {
        "name": "lemma_heads",
        "found_keys": 2,
        "total_expected": 2
      },
      {
        "name": "config_heads",
        "found_keys": 2,
        "total_expected": 2
      },
      {
        "name": "base_encoder",
        "found_keys": 280,
        "total_expected": "variable"
      }
    ],
    "warnings": [],
    "errors": []
  },
  "file_size_mb": 1083.0014581680298,
  "files_description": "- `best_gen13.pt`: PyTorch checkpoint (1083.0 MB)"
}

Citation

If you use this model, please cite the Aesop-RL project.

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