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acasal/
learn_hf_spam_not_spam_email_classifier_improved-distilbert-base-uncased

Name: learn_hf_spam_not_spam_email_classifier_improved-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_spam_not_spam_email_classifier_improved-distilbert-base-uncased

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2722
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: 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
0.6957	1.0	1	0.6490	1.0
0.6568	2.0	2	0.6109	1.0
0.5881	3.0	3	0.5939	0.8333
0.4853	4.0	4	0.5427	0.8333
0.3939	5.0	5	0.4550	1.0
0.3062	6.0	6	0.3736	1.0
0.2460	7.0	7	0.3223	1.0
0.1894	8.0	8	0.2952	1.0
0.1600	9.0	9	0.2807	1.0
0.1405	10.0	10	0.2722	1.0

Framework versions

Transformers 5.10.2
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

acasal/learn_hf_spam_not_spam_email_classifier_improved-distilbert-base-uncased

learn_hf_spam_not_spam_email_classifier_improved-distilbert-base-uncased

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

acasal/
learn_hf_spam_not_spam_email_classifier_improved-distilbert-base-uncased