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Enhance training process with improved early stopping and metrics tracking. Update README with training results and insights. Modify .gitignore to allow Metrics plots. Add plotting functionality for inference results in plotting.py. Update configuration parameters for CAPTCHA length limits.
04e423f
| import os | |
| import string | |
| from dataclasses import dataclass | |
| class Config: | |
| data_root: str = os.getenv("DATA_ROOT","Dataset_test\captchas") | |
| chars: str = string.ascii_letters + string.digits | |
| CAPTCHA_LEN_LOWER_LIMIT: int = 5 | |
| CAPTCHA_LEN_UPPER_LIMIT: int = 7 | |
| RESULT_DIR: str = "Results" | |
| # Image dimensions - increased for better character detail | |
| H: int = 60 # Increased from 48 for more vertical detail | |
| W_max: int = 256 # Increased from 224 for more time steps (T=64) | |
| grayscale: bool = True | |
| # Model architecture | |
| total_stride: int = 4 # CNN width downsampling factor | |
| # Training hyperparameters | |
| batch_size: int = 32 # Local testing | |
| batch_size_t4: int = 128 # Colab T4 recommendation | |
| num_workers: int = 4 | |
| amp: bool = True | |
| # Learning rate and optimization | |
| lr: float = 3e-4 | |
| weight_decay: float = 1e-4 | |
| # Training duration | |
| epochs: int = 40 # For 100k dataset | |
| epochs_test: int = 10 # For 1k test dataset | |
| cfg = Config() |