mbert-vifn / artifacts /seed_202_run_complete.json
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Fine-tune mBERT on ViFN: seeds [42, 22, 202]
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{
"status": "completed",
"model_key": "mbert",
"model_name": "mBERT",
"model_id": "bert-base-multilingual-cased",
"base_revision": "3f076fdb1ab68d5b2880cb87a0886f315b8146f8",
"seed": 202,
"split_seed": 42,
"smoke_test": false,
"epochs": 3,
"max_length": 256,
"micro_batch_size": 8,
"gradient_accumulation_steps": 1,
"effective_batch_size": 8,
"per_device_eval_batch_size": 8,
"text_mode_resolved": "raw",
"tokenizer_class": "BertTokenizer",
"model_class": "BertForSequenceClassification",
"model_type": "bert",
"best_checkpoint": "/content/drive/MyDrive/EACL_2027_ViFN_Benchmark/runs/mbert/full/seed_202/trainer_mb8_ga1/checkpoint-423",
"best_metric": 0.8430161943319838,
"best_model_dir": "/content/drive/MyDrive/EACL_2027_ViFN_Benchmark/runs/mbert/full/seed_202/best_model",
"train_loss": 0.3795614107280758,
"wall_seconds": 101.607901096344,
"dev_accuracy": 0.8439716312056738,
"dev_macro_precision": 0.8512345679012345,
"dev_macro_recall": 0.8434607645875252,
"dev_macro_f1": 0.8430161943319838,
"dev_weighted_f1": 0.843103052229592,
"test_accuracy": 0.8297872340425532,
"test_macro_precision": 0.8393964448119058,
"test_macro_recall": 0.8303822937625754,
"test_macro_f1": 0.828744939271255,
"test_weighted_f1": 0.8286501852011371,
"completed_at_utc": "2026-07-18T16:11:04.259760+00:00"
}