generated_from_trainer

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

scenario-kd-from-pre-finetune-silver-div-2-data-smsa-model-xlm-roberta-base

This model is a fine-tuned version of xlm-roberta-base on the smsa 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
No log 0.29 100 3.2781 0.7651 0.5383
No log 0.58 200 2.2064 0.8516 0.8093
No log 0.87 300 1.7326 0.8690 0.7949
No log 1.16 400 1.4402 0.8921 0.8520
2.4602 1.45 500 1.1721 0.9024 0.8674
2.4602 1.74 600 1.2702 0.8802 0.8257
2.4602 2.03 700 1.0680 0.9024 0.8591
2.4602 2.33 800 0.9821 0.9063 0.8646
2.4602 2.62 900 1.3768 0.8968 0.8527
0.9918 2.91 1000 0.7974 0.9087 0.8714
0.9918 3.2 1100 1.0358 0.9040 0.8615
0.9918 3.49 1200 0.9499 0.9079 0.8699
0.9918 3.78 1300 0.7355 0.9119 0.8746
0.9918 4.07 1400 0.7246 0.9167 0.8816
0.5944 4.36 1500 0.8613 0.9151 0.8778
0.5944 4.65 1600 0.7733 0.9159 0.8808
0.5944 4.94 1700 1.0419 0.9040 0.8692
0.5944 5.23 1800 0.8956 0.9056 0.8684
0.5944 5.52 1900 0.8585 0.9071 0.8692
0.4606 5.81 2000 0.7825 0.9127 0.8697
0.4606 6.1 2100 0.7634 0.9111 0.8656
0.4606 6.4 2200 0.8163 0.9151 0.8690
0.4606 6.69 2300 0.7891 0.9103 0.8686
0.4606 6.98 2400 0.6864 0.9198 0.8851
0.3809 7.27 2500 0.7646 0.9040 0.8652
0.3809 7.56 2600 0.9059 0.8984 0.8640
0.3809 7.85 2700 0.6860 0.9087 0.8632
0.3809 8.14 2800 0.7117 0.9095 0.8695
0.3809 8.43 2900 0.7996 0.9087 0.8675
0.3317 8.72 3000 0.6584 0.9127 0.8684
0.3317 9.01 3100 0.6155 0.9151 0.8835
0.3317 9.3 3200 0.6338 0.9183 0.8756
0.3317 9.59 3300 0.6210 0.9119 0.8749
0.3317 9.88 3400 0.7005 0.9151 0.8788
0.2872 10.17 3500 0.6408 0.9206 0.8842
0.2872 10.47 3600 0.5883 0.9143 0.8703
0.2872 10.76 3700 0.5575 0.9159 0.8769
0.2872 11.05 3800 0.6276 0.9143 0.8791
0.2872 11.34 3900 0.6712 0.9175 0.8720

Framework versions