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:

Loss: 0.2459
Accuracy: 0.9192
F1: 0.9192

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: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	313	0.2594	0.9133	0.9131
0.2999	2.0	626	0.2459	0.9192	0.9192

Framework versions

Transformers 4.54.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2

jnwulff/classifier-chapter4

classifier-chapter4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jnwulff/
classifier-chapter4