{
 "model": "FacebookAI/xlm-roberta-base",
 "dataset": "danielrosehill/hebrew-latin-code-switching",
 "hyperparameters": {
  "epochs": 8,
  "lr": 3e-05,
  "batch": 32,
  "seed": 20261015
 },
 "best_checkpoint": "out/checkpoint-833",
 "validation": {
  "eval_loss": 0.039957743138074875,
  "eval_precision": 0.9502617801047121,
  "eval_recall": 0.9477806788511749,
  "eval_f1": 0.9490196078431373,
  "eval_runtime": 0.2551,
  "eval_samples_per_second": 1830.853,
  "eval_steps_per_second": 31.364,
  "epoch": 8.0
 },
 "test": {
  "precision": 0.928,
  "recall": 0.9534246575342465,
  "f1": 0.9405405405405406,
  "sentences": 468
 },
 "test_generated": {
  "precision": 0.9279279279279279,
  "recall": 0.9478527607361963,
  "f1": 0.9377845220030349,
  "sentences": 430
 },
 "test_dictated": {
  "precision": 0.9285714285714286,
  "recall": 1.0,
  "f1": 0.962962962962963,
  "sentences": 38
 },
 "test_negative_sentences": {
  "sentences": 106,
  "false_positive_sentence_rate": 0.19811320754716982
 },
 "test_report": "              precision    recall  f1-score   support\n\n          HE       0.93      0.95      0.94       365\n\n   micro avg       0.93      0.95      0.94       365\n   macro avg       0.93      0.95      0.94       365\nweighted avg       0.93      0.95      0.94       365\n"
}