You can deploy this model and start earning money today!

jntak/
food_not_food_text_classifier_distilbert-base-uncased

Name: food_not_food_text_classifier_distilbert-base-uncased
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

Views

No views yet

food_not_food_text_classifier_distilbert-base-uncased

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: 0.0006
Accuracy: 1.0

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 2025
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3871	1.0	7	0.0519	1.0
0.0474	2.0	14	0.0073	1.0
0.0051	3.0	21	0.0026	1.0
0.0024	4.0	28	0.0015	1.0
0.0014	5.0	35	0.0010	1.0
0.001	6.0	42	0.0008	1.0
0.0008	7.0	49	0.0007	1.0
0.0007	8.0	56	0.0006	1.0
0.0007	9.0	63	0.0006	1.0
0.0007	10.0	70	0.0006	1.0

Framework versions

Transformers 4.54.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2

jntak/food_not_food_text_classifier_distilbert-base-uncased

food_not_food_text_classifier_distilbert-base-uncased

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jntak/
food_not_food_text_classifier_distilbert-base-uncased