| { |
| "trained": true, |
| "labels": [ |
| "action", |
| "context", |
| "method", |
| "result", |
| "measurement" |
| ], |
| "model_version": "0.1.0", |
| "max_length": 192, |
| "thresholds": [ |
| 0.5, |
| 0.5, |
| 0.5, |
| 0.5, |
| 0.5 |
| ], |
| "selected_epoch": 5, |
| "validation_macro_f1": 0.9969230769230769, |
| "experiment": { |
| "base_model": "neuralmind/bert-base-portuguese-cased", |
| "base_revision": "94d69c95f98f7d5b2a8700c420230ae10def0baa", |
| "seed": 42, |
| "epochs": 5, |
| "learning_rate": 2e-05, |
| "max_length": 192, |
| "batch_size": 8, |
| "gradient_accumulation": 2, |
| "thresholds": [ |
| 0.5, |
| 0.5, |
| 0.5, |
| 0.5, |
| 0.5 |
| ], |
| "selection": "validation_macro_f1", |
| "pooling": "attention_mask_mean", |
| "logistic_C": 1.0, |
| "logistic_max_iter": 2000 |
| }, |
| "provenance": { |
| "dataset": { |
| "dataset_version": "0.1.0", |
| "seed": 42, |
| "protocol": "compositional_groups_v1; fixed before experiments", |
| "counts": { |
| "train": 280, |
| "validation": 60, |
| "test": 60 |
| }, |
| "sha256": { |
| "dataset.jsonl": "054c0a19f2fb886c32018c1d1e8bf9b3c2ee6d32ad8f9acda58619ff5f94a9eb", |
| "splits/train.jsonl": "148466e584ac72e39e5307b6a7ab09dd7a7f2f852c51493eeb1f3bce2b13e4f0", |
| "splits/validation.jsonl": "fab146a33a5ed52e73407b687b2344b516fe1fb099b96b5b554aff00daa86306", |
| "splits/test.jsonl": "67c5244e4633f226f9d5453bac22a39e21d537d59e9b61d0ced823f97e96f176", |
| "source/development.tsv": "05a302da15ff7f13795b1b9df4bfb20928c05820b0f7c83fffeaac7687f791b8", |
| "source/test.tsv": "10d852d417b4b9b80538e807255716f566dffa0fed00dfec4f9b35e6ead72432", |
| "source/prompts.json": "56788c27df679e38ef5930a1345d17b029ca4c7ea3a5a66aa589ccd9727eabe1" |
| } |
| }, |
| "config_sha256": "55675169dcd61068fc1014f89214e65a646c546e861a20f1cba407f0337d66aa" |
| }, |
| "environment": { |
| "python": "3.11.14", |
| "platform": "Linux-7.1.8+deb13-amd64-x86_64-with-glibc2.41", |
| "packages": { |
| "torch": "2.6.0", |
| "transformers": "4.57.1", |
| "numpy": "2.3.4", |
| "scikit-learn": "1.7.2", |
| "pydantic": "2.12.4" |
| }, |
| "source_sha256": { |
| "__init__.py": "07f1e581fc9fb8256b565d0f2f968af61622da5161e441c0487e0d122d71b80e", |
| "__main__.py": "935a1c1166b0c1ea35a82256345000bf2c73ded718d77773bc27a71ecce28f7d", |
| "cli.py": "f9cc4684ec995264cf1223c79a4be5df33d6c5221d797e544f813244db90bd8b", |
| "data.py": "533b9618df7d41c1402a9fa6b02e6cd9f1ac0fdaad549d93cce98784070d52de", |
| "evaluate.py": "386dc2f86c890a3484b714e8311ce95cb771adae8a5cc91ecb266cba4e08712e", |
| "experiment.py": "683db32333171a30d6747980b705791ac17db70f6a90a8af82b6da5186b22c0e", |
| "metrics.py": "a1374b9fa54c1ae278a5b81c52317e06b6b1f97726a726afe5cfc7d924c232e3", |
| "model.py": "697d177b7634b3dbdb29731457774f80f36fd55ac23f2576d8af1a0565ce29b2", |
| "rules.py": "0c2a0dcbbac8220abfd38bc93830a699b52366e781f5b4b977329e5473d046bf", |
| "schema.py": "4afcf1dc0cf75a8eb1392a7cbbf69c6727fb566c44da94ed4e68733024c144d4", |
| "text.py": "67132ac951f1b81972229e75ca311ef8dab8dc810992f8059717528ed79bc43e" |
| } |
| } |
| } |
|
|
