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: 0.3136
Accuracy: 0.9375

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	8	0.8432	0.7188
No log	2.0	16	0.7205	0.7188
No log	3.0	24	0.6494	0.7188
No log	4.0	32	0.5616	0.7188
No log	5.0	40	0.4818	0.8438
No log	6.0	48	0.4141	0.8438
No log	7.0	56	0.3831	0.875
No log	8.0	64	0.3406	0.875
No log	9.0	72	0.3200	0.9375
No log	10.0	80	0.3136	0.9375

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

lenate/lenate_model_8

lenate_model_8

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lenate/
lenate_model_8