This model is a fine-tuned version of distilbert-base-multilingual-cased on the wnut_17 dataset.
It achieves the following results on the evaluation set:
Loss: 0.2729
Precision: 0.6122
Recall: 0.4306
F1: 0.5056
Accuracy: 0.9499
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
