| { |
| "stage": 4, |
| "dataset_id": "THemidli/applied-ner-stage4-final", |
| "base_model": "prajjwal1/bert-mini", |
| "base_revision": "5e123abc2480f0c4b4cac186d3b3f09299c258fc", |
| "tokenizer_model": "google/bert_uncased_L-2_H-128_A-2", |
| "tokenizer_revision": "30b0a37ccaaa32f332884b96992754e246e48c5f", |
| "seed": 20260802, |
| "labels": [ |
| "O", |
| "B-PERSON", |
| "I-PERSON", |
| "B-ORGANIZATION", |
| "I-ORGANIZATION", |
| "B-LOCATION", |
| "I-LOCATION", |
| "B-TIMEDATE", |
| "I-TIMEDATE", |
| "B-PRODUCT", |
| "I-PRODUCT", |
| "B-WORKOFART", |
| "I-WORKOFART", |
| "B-JOB", |
| "I-JOB", |
| "B-AMOUNT", |
| "I-AMOUNT" |
| ], |
| "parameter_count": 11109137, |
| "trainable_parameter_count": 11109137, |
| "device": "mps", |
| "platform": "macOS-27.0-arm64-arm-64bit", |
| "torch_version": "2.13.0", |
| "train_records": 841, |
| "test_records": 159, |
| "train_chunks": 865, |
| "test_chunks": 165, |
| "max_length": 256, |
| "wall_seconds": 32.908, |
| "trainer_metrics": { |
| "train_runtime": 32.8519, |
| "train_samples_per_second": 421.285, |
| "train_steps_per_second": 13.637, |
| "total_flos": 49534075078794.0, |
| "train_loss": 0.23767771824662173, |
| "epoch": 16.0 |
| }, |
| "hyperparameters": { |
| "epochs": 16, |
| "learning_rate": 0.0005, |
| "train_batch_size": 32, |
| "eval_batch_size": 64, |
| "weight_decay": 0.02, |
| "label_smoothing_factor": 0.0, |
| "warmup_steps": 45, |
| "scheduler": "linear", |
| "hidden_dropout": 0.1, |
| "attention_dropout": 0.1, |
| "classifier_dropout": 0.1 |
| }, |
| "train_overall": { |
| "overall_precision": 0.9988776655443322, |
| "overall_recall": 0.998653500897666, |
| "overall_f1": 0.9987655706430254, |
| "overall_accuracy": 0.9998373013720918 |
| }, |
| "test_overall": { |
| "overall_precision": 0.618925831202046, |
| "overall_recall": 0.6747211895910781, |
| "overall_f1": 0.6456202756780791, |
| "overall_accuracy": 0.8791745256851214 |
| }, |
| "test_f1_change_vs_stage3": 0.1771147178353455, |
| "mps_run_variance_note": "On the MPS backend, repeated runs with identical seed and config showed ±0.01–0.015 F1 variation (0.6331 vs 0.6455 across the two recorded runs); the seed is fixed, and the variation does not change the model ranking (both runs far above BERT-Tiny, slightly below ELECTRA-Small).", |
| "dataset_revision": "ce231175a828d21865c638d9718c4a6e8ba1fb1c", |
| "vocab_sha256": "07eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3" |
| } |
|
|
