Instructions to use macmacmacmac/CLEF-DualScreen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use macmacmacmac/CLEF-DualScreen with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
CLEF dual-task proper-protocol FT (seed 20261101, epoch 3) from jev-retrain MI355X run 2026-11-04
073de96 verified Download redo-training-log.jsonl from macmacmacmac/CLEF-DualScreen: direct link, hf CLI and curl.
- Browser
- Download file 6.14 kB
-
https://huggingface.co/macmacmacmac/CLEF-DualScreen/resolve/main/redo-training-log.jsonl
- Command line
-
hf download hf://macmacmacmac/CLEF-DualScreen/redo-training-log.jsonl
-
curl -L -o redo-training-log.jsonl https://huggingface.co/macmacmacmac/CLEF-DualScreen/resolve/main/redo-training-log.jsonl
6.14 kB
| {"event": "frozen_data_loaded", "data_dir": "/root/work/clef_proper", "counts": {"train": 569, "dev": 149, "test": 220}, "capped": false, "ts": 1793828091.71} | |
| {"event": "start", "device": "cuda", "train_raw": 569, "dev_raw": 149, "test_raw": 220, "lr": 0.0001, "epochs": 3, "batch": 16, "pos_weight": 3.0, "ts": 1793828091.71} | |
| {"event": "cache_only_mode", "litert_graphs": 0, "note": "hidden states pre-encoded with pinned PyTorch clef-flash on CUDA", "ts": 1793828092.46} | |
| {"event": "model_loaded", "trainable_params": 121762820, "state_dict_params": 121762820, "source": "runtime_state_dict", "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 20, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 40, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 60, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 80, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 100, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 120, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 140, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.46} | |
| {"event": "prep_dev", "done": 149, "of": 149, "elapsed_min": 0.0, "ts": 1793828092.47} | |
| {"event": "frozen_data_loaded", "data_dir": "/root/work/clef_proper", "counts": {"train": 569, "dev": 149, "test": 220}, "capped": false, "ts": 1793828123.56} | |
| {"event": "start", "device": "cuda", "train_raw": 569, "dev_raw": 149, "test_raw": 220, "lr": 0.0001, "epochs": 3, "batch": 16, "pos_weight": 3.0, "ts": 1793828123.56} | |
| {"event": "cache_only_mode", "litert_graphs": 0, "note": "hidden states pre-encoded with pinned PyTorch clef-flash on CUDA", "ts": 1793828124.31} | |
| {"event": "model_loaded", "trainable_params": 121762820, "state_dict_params": 121762820, "source": "runtime_state_dict", "ts": 1793828124.31} | |
| {"event": "prep_dev", "done": 20, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.33} | |
| {"event": "prep_dev", "done": 40, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.35} | |
| {"event": "prep_dev", "done": 60, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.37} | |
| {"event": "prep_dev", "done": 80, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.39} | |
| {"event": "prep_dev", "done": 100, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.41} | |
| {"event": "prep_dev", "done": 120, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.43} | |
| {"event": "prep_dev", "done": 140, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.45} | |
| {"event": "prep_dev", "done": 149, "of": 149, "elapsed_min": 0.0, "ts": 1793828124.46} | |
| {"event": "eval", "split": "dev", "epoch": 0, "step": 0, "loss": 0.4123, "tool_output_filter": {"n": 65, "pos": 35, "neg": 30, "auc": 0.9781, "tpr@0.5": 0.9143, "fpr@0.5": 0.0667, "tpr@0.9": 0.6857, "fpr@0.9": 0.0333, "tpr@0.99": 0.0, "fpr@0.99": 0.0}, "action_authorization_guard": {"n": 84, "pos": 39, "neg": 45, "auc": 0.9704, "tpr@0.35": 0.8974, "fpr@0.35": 0.0, "tpr@0.5": 0.8462, "fpr@0.5": 0.0, "tpr@0.9": 0.0, "fpr@0.9": 0.0}, "elapsed_min": 0.08, "ts": 1793828129.33} | |
| {"event": "eval", "split": "dev", "epoch": 1, "step": 36, "loss": 0.2666, "tool_output_filter": {"n": 65, "pos": 35, "neg": 30, "auc": 0.9819, "tpr@0.5": 0.9429, "fpr@0.5": 0.0667, "tpr@0.9": 0.8857, "fpr@0.9": 0.0333, "tpr@0.99": 0.7143, "fpr@0.99": 0.0333}, "action_authorization_guard": {"n": 84, "pos": 39, "neg": 45, "auc": 0.9726, "tpr@0.35": 1.0, "fpr@0.35": 0.3778, "tpr@0.5": 0.9487, "fpr@0.5": 0.2444, "tpr@0.9": 0.8462, "fpr@0.9": 0.0}, "elapsed_min": 0.55, "ts": 1793828157.3} | |
| {"event": "saved_best", "epoch": 1, "step": 36, "comb_auc": 0.9772, "ts": 1793828157.49} | |
| {"event": "step", "epoch": 2, "step": 72, "of": 108, "encoded_train": 568, "train_total": 568, "loss": 0.4582, "lr": 3.63e-05, "elapsed_min": 0.93, "ts": 1793828179.85} | |
| {"event": "eval", "split": "dev", "epoch": 2, "step": 72, "loss": 0.2031, "tool_output_filter": {"n": 65, "pos": 35, "neg": 30, "auc": 0.9838, "tpr@0.5": 0.9429, "fpr@0.5": 0.0667, "tpr@0.9": 0.8571, "fpr@0.9": 0.0333, "tpr@0.99": 0.6571, "fpr@0.99": 0.0333}, "action_authorization_guard": {"n": 84, "pos": 39, "neg": 45, "auc": 0.9818, "tpr@0.35": 0.9744, "fpr@0.35": 0.2667, "tpr@0.5": 0.9487, "fpr@0.5": 0.1111, "tpr@0.9": 0.8718, "fpr@0.9": 0.0}, "elapsed_min": 0.99, "ts": 1793828183.92} | |
| {"event": "saved_best", "epoch": 2, "step": 72, "comb_auc": 0.9828, "ts": 1793828184.16} | |
| {"event": "step", "epoch": 3, "step": 108, "of": 108, "encoded_train": 568, "train_total": 568, "loss": 0.008, "lr": 1e-05, "elapsed_min": 1.37, "ts": 1793828206.4} | |
| {"event": "eval", "split": "dev", "epoch": 3, "step": 108, "loss": 0.1566, "tool_output_filter": {"n": 65, "pos": 35, "neg": 30, "auc": 0.9829, "tpr@0.5": 0.9714, "fpr@0.5": 0.0667, "tpr@0.9": 0.8857, "fpr@0.9": 0.0333, "tpr@0.99": 0.6857, "fpr@0.99": 0.0333}, "action_authorization_guard": {"n": 84, "pos": 39, "neg": 45, "auc": 0.9846, "tpr@0.35": 0.9744, "fpr@0.35": 0.0889, "tpr@0.5": 0.9231, "fpr@0.5": 0.0889, "tpr@0.9": 0.8974, "fpr@0.9": 0.0}, "elapsed_min": 1.44, "ts": 1793828210.45} | |
| {"event": "saved_best", "epoch": 3, "step": 108, "comb_auc": 0.9838, "ts": 1793828210.7} | |
| {"event": "prep_test", "done": 20, "of": 220, "elapsed_min": 1.44, "ts": 1793828210.74} | |
| {"event": "prep_test", "done": 40, "of": 220, "elapsed_min": 1.44, "ts": 1793828210.76} | |
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| {"event": "prep_test", "done": 220, "of": 220, "elapsed_min": 1.44, "ts": 1793828210.88} | |