generated_from_trainer

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006-microsoft-deberta-v3-base-finetuned-yahoo-80_20k

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
1.0576 0.5 1250 0.8850 0.7207 0.727 0.7338 0.727 4.0147 83.4807 2.0903 34.3125 39.5640 26 24.9911 78.1898
0.853 1.0 2500 0.8239 0.7432 0.7461 0.7462 0.7461 4.0251 83.4807 2.0903 34.3125 39.5640 26 24.9919 78.1898
0.7364 1.5 3750 0.8151 0.7429 0.7478 0.7431 0.7478 4.0743 83.4807 2.0903 34.3125 39.5640 25 29.8278 78.1898
0.7345 2.0 5000 0.8102 0.7433 0.7470 0.7460 0.7470 4.0763 83.4807 2.0903 34.3125 39.5640 27 29.8285 78.1898
0.6184 2.5 6250 0.8222 0.7498 0.7518 0.7505 0.7518 4.0937 83.4807 2.0903 34.3125 39.5640 27 33.9630 78.1898
0.6174 3.0 7500 0.8322 0.7516 0.7545 0.7530 0.7545 4.0717 83.4807 2.0903 34.3125 39.5640 25 33.9634 78.1898
0.5036 3.5 8750 0.8948 0.7435 0.7476 0.7428 0.7476 4.1335 83.4807 2.0903 34.3125 39.5640 26 38.0971 78.1898
0.5149 4.0 10000 0.8892 0.7416 0.7451 0.7433 0.7451 4.1251 83.4807 2.0903 34.3125 39.5640 26 38.0980 78.1898
0.4106 4.5 11250 0.9957 0.7336 0.7345 0.7348 0.7345 4.1319 83.4807 2.0903 34.3125 39.5640 24 40.1601 78.1898
0.407 5.0 12500 0.9997 0.7318 0.7344 0.7332 0.7344 4.1372 83.4807 2.0903 34.3125 39.5640 25 40.1605 78.1898
0.3195 5.5 13750 1.0747 0.7320 0.736 0.7318 0.736 4.1359 83.4807 2.0903 34.3125 39.5640 25 42.2225 78.1898
0.3281 6.0 15000 1.1199 0.7300 0.7323 0.7313 0.7323 4.1438 83.4807 2.0903 34.3125 39.5640 26 42.2234 78.1898
0.2519 6.5 16250 1.2232 0.7299 0.7321 0.7295 0.7321 4.1640 83.4807 2.0903 34.3125 39.5640 26 42.2237 78.1898
0.2482 7.0 17500 1.2532 0.7274 0.7272 0.7282 0.7272 4.1578 83.4807 2.0903 34.3125 39.5640 26 42.2238 78.1898
0.1939 7.5 18750 1.3487 0.7222 0.7248 0.7215 0.7248 4.1702 83.4807 2.0903 34.3125 39.5640 26 42.2241 78.1898
0.1992 8.0 20000 1.3886 0.7197 0.7186 0.7218 0.7186 4.1572 83.4807 2.0903 34.3125 39.5640 27 42.2247 78.1898
0.1511 8.5 21250 1.4716 0.7197 0.7195 0.7204 0.7195 4.1566 83.4807 2.0903 34.3125 39.5640 25 42.2249 78.1898
0.1563 9.0 22500 1.4829 0.7223 0.7237 0.7221 0.7237 4.1650 83.4807 2.0903 34.3125 39.5640 27 42.2249 78.1898
0.1286 9.5 23750 1.5533 0.7210 0.7217 0.7210 0.7217 4.1784 83.4807 2.0903 34.3125 39.5640 26 42.2251 78.1898
0.1223 10.0 25000 1.5718 0.7212 0.7212 0.7217 0.7212 4.1618 83.4807 2.0903 34.3125 39.5640 26 42.2251 78.1898

Framework versions