train -s 0 -v 4 file.txt model.m

iter  1 act 7.244e+02 pre 6.621e+02 delta 1.606e+01 f 1.298e+03 |g| 1.206e+02 CG   4
iter  2 act 5.081e+01 pre 4.454e+01 delta 1.606e+01 f 5.738e+02 |g| 2.451e+01 CG   3
iter  3 act 4.115e+00 pre 3.822e+00 delta 1.606e+01 f 5.230e+02 |g| 5.738e+00 CG   2
iter  4 act 9.279e-02 pre 9.179e-02 delta 1.606e+01 f 5.189e+02 |g| 7.476e-01 CG   2
iter  1 act 7.247e+02 pre 6.630e+02 delta 1.621e+01 f 1.298e+03 |g| 1.208e+02 CG   4
iter  2 act 4.910e+01 pre 4.285e+01 delta 1.621e+01 f 5.736e+02 |g| 2.449e+01 CG   2
iter  3 act 4.888e+00 pre 4.575e+00 delta 1.621e+01 f 5.245e+02 |g| 5.872e+00 CG   2
iter  4 act 1.267e-01 pre 1.249e-01 delta 1.621e+01 f 5.196e+02 |g| 8.635e-01 CG   2
iter  1 act 7.304e+02 pre 6.676e+02 delta 1.604e+01 f 1.298e+03 |g| 1.229e+02 CG   4
iter  2 act 5.173e+01 pre 4.521e+01 delta 1.604e+01 f 5.679e+02 |g| 2.511e+01 CG   3
iter  3 act 4.441e+00 pre 4.108e+00 delta 1.604e+01 f 5.161e+02 |g| 5.999e+00 CG   2
iter  4 act 1.034e-01 pre 1.021e-01 delta 1.604e+01 f 5.117e+02 |g| 7.984e-01 CG   2
iter  1 act 7.130e+02 pre 6.498e+02 delta 1.560e+01 f 1.298e+03 |g| 1.191e+02 CG   3
iter  2 act 5.452e+01 pre 4.824e+01 delta 1.560e+01 f 5.845e+02 |g| 2.485e+01 CG   3
iter  3 act 4.263e+00 pre 3.944e+00 delta 1.560e+01 f 5.300e+02 |g| 5.887e+00 CG   2
iter  4 act 1.029e-01 pre 1.014e-01 delta 1.560e+01 f 5.258e+02 |g| 8.024e-01 CG   2
Accuracy = 93.1117% (2325/2497)
F-score = 0.414966
Recall = 26.8722% (61/227)
Precision = 91.0448% (61/67)