This model is a fine-tuned version of distilbert-base-cased on yyu/amazon-attrprompt dataset. It achieves the following results on the evaluation set:

Loss: 1.9022
Accuracy: {'accuracy': 0.7478260869565218}
F1 Score: {'f1': 0.7350319489971969}

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
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score
0.2514	1.0	1728	1.8422	{'accuracy': 0.7347826086956522}	{'f1': 0.7217427746565059}
0.2709	2.0	3456	1.8755	{'accuracy': 0.7347826086956522}	{'f1': 0.7200496580345588}
0.0912	3.0	5184	1.9022	{'accuracy': 0.7478260869565218}	{'f1': 0.7350319489971969}

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0

Asteriks/distilbert-cased-reviews-v1

distilbert-cased-reviews-v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Asteriks/
distilbert-cased-reviews-v1