ntc-scv-distilbert-base-uncased – AI Model by thainq107 | AlphaNeural AI

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thainq107/
ntc-scv-distilbert-base-uncased

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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ntc-scv-distilbert-base-uncased

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3672
Accuracy: 0.8458

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: 256
eval_batch_size: 256
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
No log	1.0	118	0.4574	0.7902
No log	2.0	236	0.4322	0.8045
No log	3.0	354	0.4200	0.8121
No log	4.0	472	0.3952	0.8271
0.4318	5.0	590	0.3981	0.8312
0.4318	6.0	708	0.3887	0.8343
0.4318	7.0	826	0.4038	0.8316
0.4318	8.0	944	0.4085	0.8333
0.3168	9.0	1062	0.4098	0.835
0.3168	10.0	1180	0.4104	0.8362

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0