results – AI Model by mihail11 | AlphaNeural AI

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mihail11/
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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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results

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: 0.0085
Accuracy: 0.995
Precision: 0.9950
Recall: 0.995
F1: 0.9950

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.3846	1.0	100	0.0655	0.975	0.9754	0.975	0.9750
0.0399	2.0	200	0.0389	0.985	0.9854	0.985	0.9850
0.0124	3.0	300	0.0183	0.995	0.9950	0.995	0.9950
0.0118	4.0	400	0.0082	0.995	0.9950	0.995	0.9950
0.0014	5.0	500	0.0085	0.995	0.9950	0.995	0.9950

Framework versions

Transformers 4.45.1
Pytorch 2.4.1+cpu
Datasets 3.0.1
Tokenizers 0.20.0