xlm-roberta-base-afr-MICRO

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2268
  • F1: 0.7405
  • Roc Auc: 0.8537
  • Accuracy: 0.6918

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:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
0.3224 1.0 120 0.3133 0.0 0.5 0.3627
0.317 2.0 240 0.3122 0.0 0.5 0.3627
0.2939 3.0 360 0.3043 0.0 0.5 0.3627
0.2914 4.0 480 0.3057 0.1170 0.5309 0.4046
0.2698 5.0 600 0.2474 0.5582 0.7111 0.5870
0.2265 6.0 720 0.2290 0.6752 0.7933 0.6730
0.1913 7.0 840 0.2479 0.6212 0.7753 0.5975
0.136 8.0 960 0.2088 0.6968 0.8041 0.6688
0.1243 9.0 1080 0.2222 0.7027 0.8106 0.6646
0.1106 10.0 1200 0.2118 0.7245 0.8289 0.6855
0.0829 11.0 1320 0.2289 0.6836 0.7870 0.6583
0.0835 12.0 1440 0.2250 0.6947 0.8026 0.6541
0.0801 13.0 1560 0.2180 0.7334 0.8467 0.6918
0.049 14.0 1680 0.2308 0.7055 0.8081 0.6688
0.0575 15.0 1800 0.2268 0.7405 0.8537 0.6918
0.0474 16.0 1920 0.2315 0.7158 0.8311 0.6751
0.0522 17.0 2040 0.2330 0.7064 0.8217 0.6667
0.0468 18.0 2160 0.2301 0.7265 0.8388 0.6792
0.0405 19.0 2280 0.2285 0.7259 0.8366 0.6813

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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