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Trial timestamp (UTC): 2025-10-07 14:29:04
| Hyperparameter | Value |
|---|---|
| LR | 2e-05 |
| EPOCHS | 3 |
| MAX_LENGTH | 256 |
| USE_BIO | True |
| USE_LANG_TOKEN | False |
| GATED_BIO | True |
| FOCAL_LOSS | True |
| FOCAL_GAMMA | 1.5 |
| USE_SAMPLER | True |
| R_DROP | True |
| R_KL_ALPHA | 1.0 |
| Metric | Value |
|---|---|
| trial | 2 |
| cfg | {'LR': 2e-05, 'EPOCHS': 3.0, 'MAX_LENGTH': 256.0, 'USE_BIO': 1.0, 'USE_LANG_TOKEN': 0.0, 'GATED_BIO': 1.0, 'FOCAL_LOSS': 1.0, 'FOCAL_GAMMA': 1.5, 'USE_SAMPLER': 1.0, 'R_DROP': 1.0, 'R_KL_ALPHA': 1.0} |
| f1_macro_dev | 0.7577947998705361 |
| best_threshold_dev | 0.9 |
| precision_macro_dev | 0.919155072955548 |
| recall_macro_dev | 0.7005275974025974 |
train_en.csv, train_it.csv, train_es.csv with 15% stratified Dev).1from transformers import AutoTokenizer, AutoModelForSequenceClassification
2tok = AutoTokenizer.from_pretrained("SimoneAstarita/october-project-first-sweep-20251007-142904-t02")
3model = AutoModelForSequenceClassification.from_pretrained("SimoneAstarita/october-project-first-sweep-20251007-142904-t02")