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Training config
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Model name : castorini/afriberta_base
Tokenizer name : castorini/afriberta_base
Number of labels : 22
Batch size : 8
Learning rate : 5e-05
Number of epochs : 16
Random seed : 42

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Epoch 1
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Traning loss : 818.2853
Validation loss : 0.1867
Precision : 0.8856
Recall : 0.8025
F1-score : 0.8285
Checkpoint saved

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Epoch 2
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Traning loss : 245.6919
Validation loss : 0.1653
Precision : 0.9115
Recall : 0.7915
F1-score : 0.8174

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Epoch 3
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Traning loss : 124.5959
Validation loss : 0.1279
Precision : 0.9503
Recall : 0.8683
F1-score : 0.8944
Checkpoint saved

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Epoch 4
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Traning loss : 76.5310
Validation loss : 0.2006
Precision : 0.9543
Recall : 0.8714
F1-score : 0.8966
Checkpoint saved

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Epoch 5
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Traning loss : 55.0676
Validation loss : 0.1981
Precision : 0.9374
Recall : 0.8800
F1-score : 0.8927

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Epoch 6
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Traning loss : 36.3393
Validation loss : 0.1937
Precision : 0.9037
Recall : 0.8220
F1-score : 0.8429

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Epoch 7
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Traning loss : 21.6568
Validation loss : 0.1819
Precision : 0.8993
Recall : 0.8509
F1-score : 0.8652
Early stopping triggered