generated_from_trainer

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NoDuplicates

This model is a fine-tuned version of distilbert-base-uncased 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 Class 0 F1 Class 1 F1 Class 2 F1 Class 3 F1 Class 4 F1 Class 5 F1 Class 6 F1 Class 7 F1 Class 8 F1 Class 9 F1 Class 10 F1 Class 11 F1 Class 12 F1 Class 13 F1 Class 14 F1 Class 15 F1 Class 16 F1 Class 17 F1 Class 18 F1 Class 19
1.4862 0.27 300 0.8201 0.7845 0.4484 0.8675 0.0 0.8627 0.0 0.6733 0.0 0.6627 0.0 0.0 0.9862 0.1935 0.9600 0.8299 0.0833 0.2353 0.24 0.0400 0.8852 0.9451 0.5033
0.7269 0.53 600 0.5951 0.8491 0.6504 0.9048 0.0 0.8567 0.0 0.7596 0.6111 0.6887 0.0 0.0 0.9877 0.8033 0.9286 0.8798 0.9167 0.74 0.6857 0.5823 0.9506 0.9485 0.7640
0.5429 0.8 900 0.5375 0.8637 0.7086 0.8904 0.0 0.8589 0.0 0.7254 0.7805 0.8215 0.6769 0.0 0.9877 0.7833 1.0 0.9022 0.9130 0.7912 0.7733 0.7048 0.9032 0.9474 0.7119
0.4594 1.06 1200 0.5110 0.8805 0.7113 0.9099 0.0 0.8925 0.0 0.7706 0.7391 0.8139 0.4091 0.0 0.9908 0.8785 1.0 0.8983 0.8936 0.8090 0.7556 0.7907 0.9529 0.9574 0.7647
0.3484 1.33 1500 0.4679 0.8951 0.7667 0.9180 0.0 0.9080 0.6957 0.8 0.7619 0.8299 0.6875 0.0 0.9908 0.8909 1.0 0.9196 0.9130 0.8172 0.7865 0.7527 0.9398 0.9474 0.7755
0.3744 1.59 1800 0.4359 0.8951 0.7774 0.9290 0.0 0.8815 0.8462 0.8049 0.7805 0.8449 0.7059 0.0 0.9908 0.9346 1.0 0.9143 0.8980 0.8387 0.7475 0.7179 0.9647 0.9583 0.7895
0.3514 1.86 2100 0.5161 0.8903 0.7592 0.9109 0.0 0.8973 0.6429 0.7603 0.7907 0.8571 0.7077 0.0 0.9908 0.9346 1.0 0.8971 0.8936 0.7042 0.7324 0.7857 0.9595 0.9574 0.7609
0.3111 2.12 2400 0.4327 0.9080 0.8027 0.9283 0.3333 0.9141 0.7407 0.8207 0.8095 0.8622 0.7606 0.0 0.9908 0.9298 0.9630 0.9215 0.9167 0.8041 0.8 0.8132 0.9651 0.9574 0.8224
0.2088 2.39 2700 0.4356 0.9128 0.8452 0.9386 0.3333 0.9058 0.8462 0.8265 0.8 0.8562 0.7429 0.7500 0.9893 0.9346 0.9630 0.9322 0.8936 0.8205 0.8372 0.7765 0.9651 0.9574 0.8350
0.2317 2.65 3000 0.4294 0.9137 0.8217 0.9365 0.3333 0.9102 0.625 0.8243 0.8293 0.875 0.8056 0.3333 0.9893 0.9444 0.9630 0.9284 0.8980 0.8478 0.8471 0.7816 0.9651 0.9574 0.8400
0.1816 2.92 3300 0.4279 0.9128 0.8384 0.9406 0.3333 0.9127 0.6471 0.8254 0.8293 0.8767 0.7606 0.7500 0.9878 0.9444 0.9630 0.9265 0.8980 0.8444 0.8132 0.7778 0.9651 0.9574 0.8148

Framework versions