generated_from_trainer

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015-microsoft-deberta-v3-base-finetuned-yahoo-80_20

This model is a fine-tuned version of microsoft/deberta-v3-base 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 F1 Accuracy Precision Recall System Ram Used System Ram Total Gpu Ram Allocated Gpu Ram Cached Gpu Ram Total Gpu Utilization Disk Space Used Disk Space Total
2.3062 2.0 6 2.3028 0.025 0.1 0.0143 0.1 3.9009 83.4807 2.0874 6.8398 39.5640 51 24.7819 78.1898
2.304 4.0 12 2.3020 0.0722 0.15 0.0625 0.15 3.9032 83.4807 2.0873 6.8418 39.5640 56 24.7819 78.1898
2.2892 6.0 18 2.2997 0.0111 0.05 0.0063 0.05 3.9136 83.4807 2.0874 6.8418 39.5640 62 24.7819 78.1898
2.2729 8.0 24 2.2947 0.0190 0.1 0.0105 0.1 3.9411 83.4807 2.0873 6.8418 39.5640 56 24.7819 78.1898
2.2108 10.0 30 2.2843 0.0521 0.15 0.0333 0.15 3.9439 83.4807 2.0873 6.8418 39.5640 60 24.7819 78.1898
2.1482 12.0 36 2.2660 0.1417 0.2 0.1643 0.2 3.9451 83.4807 2.0873 6.8418 39.5640 48 24.7819 78.1898
2.0203 14.0 42 2.2328 0.2086 0.3 0.1617 0.3 3.9597 83.4807 2.0874 6.8418 39.5640 52 24.7819 78.1898
1.8707 16.0 48 2.2030 0.2019 0.3 0.1533 0.3 3.9691 83.4807 2.0873 6.8418 39.5640 55 24.7819 78.1898
1.701 18.0 54 2.1741 0.2638 0.35 0.2483 0.35 3.9705 83.4807 2.0873 6.8418 39.5640 58 24.7819 78.1898
1.5493 20.0 60 2.1379 0.2967 0.35 0.3 0.35 3.9699 83.4807 2.0874 6.8516 39.5640 57 24.7819 78.1898
1.4073 22.0 66 2.1232 0.2244 0.3 0.1952 0.3 3.9711 83.4807 2.0873 6.8516 39.5640 51 24.7819 78.1898
1.2447 24.0 72 2.1096 0.2344 0.3 0.2119 0.3 3.9705 83.4807 2.0873 6.8516 39.5640 49 24.7819 78.1898
1.155 26.0 78 2.0978 0.3178 0.4 0.3119 0.4 3.9663 83.4807 2.0874 6.8516 39.5640 56 24.7819 78.1898
1.0522 28.0 84 2.0805 0.2744 0.35 0.2452 0.35 3.9661 83.4807 2.0873 6.8516 39.5640 63 24.7820 78.1898
0.9741 30.0 90 2.0735 0.2744 0.35 0.2452 0.35 3.9575 83.4807 2.0873 6.8516 39.5640 59 24.7820 78.1898
0.9042 32.0 96 2.0793 0.2744 0.35 0.2452 0.35 3.9661 83.4807 2.0873 6.8516 39.5640 50 24.7820 78.1898
0.8497 34.0 102 2.0769 0.2744 0.35 0.2452 0.35 3.9654 83.4807 2.0874 6.8516 39.5640 58 24.7820 78.1898
0.8228 36.0 108 2.0736 0.2744 0.35 0.2452 0.35 3.9660 83.4807 2.0873 6.8516 39.5640 60 24.7820 78.1898
0.7908 38.0 114 2.0717 0.2744 0.35 0.2452 0.35 3.9659 83.4807 2.0873 6.8516 39.5640 59 24.7820 78.1898
0.7998 40.0 120 2.0709 0.2744 0.35 0.2452 0.35 3.9661 83.4807 2.0873 6.8516 39.5640 59 24.7820 78.1898

Framework versions