This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the naamapadam dataset.
It achieves the following results on the evaluation set:
Loss: nan
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.8213
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: 0.0005
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
