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: 0.1215
Accuracy: 0.9688

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 11

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	10	0.8277	0.625
No log	2.0	20	0.6681	0.775
No log	3.0	30	0.5125	0.8688
No log	4.0	40	0.3817	0.8938
No log	5.0	50	0.2871	0.925
No log	6.0	60	0.2268	0.9313
No log	7.0	70	0.1862	0.9313
No log	8.0	80	0.1553	0.9375
No log	9.0	90	0.1365	0.9563
No log	10.0	100	0.1253	0.9688
No log	11.0	110	0.1215	0.9688

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

lenate/lenate_model_6

lenate_model_6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lenate/
lenate_model_6