This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
eval_loss: 0.5640
eval_model_preparation_time: 0.0016
eval_accuracy: 0.67
eval_precision: 0.6410
eval_recall: 0.7576
eval_f1: 0.6944
eval_runtime: 0.8174
eval_samples_per_second: 244.681
eval_steps_per_second: 30.585
step: 0
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: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
