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ppak10/
defect-classification-distilbert-baseline-10-epochs

Name: defect-classification-distilbert-baseline-10-epochs
Availability: InStock

transformers

safetensors

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

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defect-classification-distilbert-baseline-10-epochs

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: 0.2976
Accuracy: 0.8762

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: 512
eval_batch_size: 512
seed: 42
optimizer: Use 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
0.6008	1.0	1062	0.5867	0.7578
0.4986	2.0	2124	0.4298	0.8051
0.4322	3.0	3186	0.3786	0.8255
0.458	4.0	4248	0.3425	0.8462
0.4143	5.0	5310	0.3274	0.8533
0.4443	6.0	6372	0.3153	0.8620
0.3508	7.0	7434	0.3076	0.8691
0.4489	8.0	8496	0.2989	0.8745
0.364	9.0	9558	0.2974	0.8764
0.4091	10.0	10620	0.2976	0.8762

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

ppak10/defect-classification-distilbert-baseline-10-epochs

defect-classification-distilbert-baseline-10-epochs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ppak10/
defect-classification-distilbert-baseline-10-epochs