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: 0.0005
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: 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
0.4263	1.0	7	0.1215	1.0
0.0757	2.0	14	0.0092	1.0
0.0074	3.0	21	0.0025	1.0
0.0023	4.0	28	0.0013	1.0
0.0013	5.0	35	0.0008	1.0
0.001	6.0	42	0.0007	1.0
0.0008	7.0	49	0.0006	1.0
0.0007	8.0	56	0.0005	1.0
0.0006	9.0	63	0.0005	1.0
0.0006	10.0	70	0.0005	1.0

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

sallyakti/learn_hf_food_or_not_food_text_classifier-distilbert-base-uncased

learn_hf_food_or_not_food_text_classifier-distilbert-base-uncased

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sallyakti/
learn_hf_food_or_not_food_text_classifier-distilbert-base-uncased