After running an experiment, you will see your run folder populated with many files and folders. Here's a quick run-down of what they are:
args.json: Saved a copy of your run arguments for future reference.last_model.p: Model weights at the end of training.last_model.metadata.json: Contains the metadata for the best-model-weights (e.g. last step of training).best_model.p: The best version of the model weights based on validation-subset,best_model.metadata.json: Contains the metadata for the best-model-weights (e.g. what step of training they were from, validation scores at that point).checkpoint.p: A checkpoint for the run that allows you to resume interrupted runs. Contains additional training state, such as the optimizer state, so it's at least 2x as large as model weights.{log-timestamp}/loss_train.zlog: JSONL log of training loss over training steps{log-timestamp}/early_stopping.zlog: JSONL log of early-stopping progress (e.g. steps since last best model){log-timestamp}/train_val.zlog: JSONL log of validation-subset evaluation over the course of training (i.e. what's used for early stopping){log-timestamp}/train_val_best.zlog: JSONL log of validation-subset evaluation, only recording the improving runs