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2026hbk/
learn_hf_food_not_food_text_classifer_distilbert-base-uncased

Name: learn_hf_food_not_food_text_classifer_distilbert-base-uncased
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

text-embeddings-inference

endpoints_compatible

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learn_hf_food_not_food_text_classifer_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: 0.0017
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: 0.001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
0.9001	1.0	7	1.1240	0.34
0.3689	2.0	14	0.0104	1.0
0.1381	3.0	21	0.0034	1.0
0.0580	4.0	28	0.0499	0.98
0.0365	5.0	35	0.0068	1.0
0.0578	6.0	42	0.0028	1.0
0.0717	7.0	49	0.0066	1.0
0.0283	8.0	56	0.0037	1.0
0.0273	9.0	63	0.0019	1.0
0.0244	10.0	70	0.0017	1.0

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu129
Datasets 4.5.0
Tokenizers 0.22.2

2026hbk/learn_hf_food_not_food_text_classifer_distilbert-base-uncased

learn_hf_food_not_food_text_classifer_distilbert-base-uncased

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

2026hbk/
learn_hf_food_not_food_text_classifer_distilbert-base-uncased