***Only 300 samples were used due to time limitations
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
eval_loss: 0.3936
eval_model_preparation_time: 0.0032
eval_accuracy: 0.8333
eval_f1: 0.8397
eval_runtime: 191.9771
eval_samples_per_second: 1.563
eval_steps_per_second: 1.563
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: 1
eval_batch_size: 1
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
