generated_from_trainer

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bank-transactions-statements-classification

This model is a fine-tuned version of flaubert/flaubert_small_cased on the None dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Macro F1 Weighted
No log 0.29 50 3.6955 0.1012 0.0238 0.0880
No log 0.58 100 3.2965 0.2150 0.0569 0.1598
No log 0.87 150 3.1122 0.2530 0.0833 0.1889
No log 1.16 200 2.6838 0.3622 0.1800 0.3051
No log 1.45 250 2.5128 0.3808 0.1938 0.3139
No log 1.74 300 2.1573 0.4913 0.3241 0.4522
No log 2.03 350 2.0208 0.5220 0.3910 0.4832
No log 2.33 400 2.0454 0.5053 0.4090 0.4613
No log 2.62 450 1.7601 0.5599 0.4682 0.5303
3.1338 2.91 500 1.6837 0.5965 0.5489 0.5736
3.1338 3.2 550 1.6337 0.5885 0.5744 0.5609
3.1338 3.49 600 1.4553 0.6491 0.6219 0.6322
3.1338 3.78 650 1.4483 0.6531 0.6441 0.6345
3.1338 4.07 700 1.4108 0.6625 0.6810 0.6522
3.1338 4.36 750 1.3241 0.6924 0.6999 0.6769
3.1338 4.65 800 1.3254 0.6824 0.6960 0.6703
3.1338 4.94 850 1.3349 0.6937 0.6952 0.6759
3.1338 5.23 900 1.2264 0.7057 0.7157 0.6931
3.1338 5.52 950 1.3012 0.6891 0.7061 0.6748
1.6259 5.81 1000 1.2756 0.7071 0.7224 0.6925
1.6259 6.1 1050 1.1432 0.7317 0.7440 0.7267
1.6259 6.4 1100 1.2014 0.7290 0.7434 0.7161
1.6259 6.69 1150 1.1029 0.7483 0.7656 0.7367
1.6259 6.98 1200 1.1643 0.7310 0.7470 0.7227
1.6259 7.27 1250 1.1112 0.7477 0.7561 0.7371
1.6259 7.56 1300 1.1662 0.7350 0.7668 0.7254
1.6259 7.85 1350 1.0756 0.7577 0.7823 0.7530
1.6259 8.14 1400 1.1390 0.7403 0.7657 0.7318
1.6259 8.43 1450 1.1555 0.7437 0.7637 0.7377
1.092 8.72 1500 1.1086 0.7437 0.7686 0.7384
1.092 9.01 1550 1.0789 0.7510 0.7780 0.7427
1.092 9.3 1600 1.0613 0.7543 0.7823 0.7492
1.092 9.59 1650 1.0750 0.7477 0.7701 0.7382
1.092 9.88 1700 1.1412 0.7423 0.7772 0.7349
1.092 10.17 1750 1.0580 0.7617 0.7918 0.7549
1.092 10.47 1800 1.0667 0.7670 0.7856 0.7580
1.092 10.76 1850 1.1344 0.7403 0.7757 0.7332
1.092 11.05 1900 1.0808 0.7603 0.7944 0.7571
1.092 11.34 1950 1.0367 0.7690 0.7932 0.7655
0.9029 11.63 2000 1.0921 0.7577 0.7861 0.7504
0.9029 11.92 2050 1.0833 0.7603 0.7912 0.7541
0.9029 12.21 2100 1.0523 0.7716 0.7968 0.7662
0.9029 12.5 2150 1.0467 0.7683 0.7939 0.7614
0.9029 12.79 2200 1.0515 0.7703 0.7987 0.7667
0.9029 13.08 2250 1.0604 0.7696 0.8020 0.7654
0.9029 13.37 2300 1.0900 0.7716 0.8002 0.7663
0.9029 13.66 2350 1.0348 0.7743 0.8009 0.7686
0.9029 13.95 2400 1.0495 0.7656 0.7929 0.7610
0.9029 14.24 2450 1.0411 0.7670 0.7956 0.7624
0.7924 14.53 2500 1.0458 0.7683 0.7945 0.7635
0.7924 14.83 2550 1.0401 0.7696 0.7982 0.7649

Framework versions