distilbert_sst2_padding40model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst2_padding40model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding40model

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: 0.8990
Accuracy: 0.8984

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	433	0.2807	0.8918
0.352	2.0	866	0.2839	0.8984
0.1741	3.0	1299	0.4073	0.8979
0.0814	4.0	1732	0.5104	0.9039
0.0415	5.0	2165	0.8648	0.8693
0.0268	6.0	2598	0.6747	0.8957
0.0204	7.0	3031	0.7511	0.8940
0.0204	8.0	3464	0.6485	0.9017
0.0195	9.0	3897	0.8488	0.8929
0.0042	10.0	4330	0.8213	0.9001
0.0097	11.0	4763	0.8371	0.8979
0.0069	12.0	5196	0.9002	0.8935
0.0108	13.0	5629	0.8321	0.8973
0.0072	14.0	6062	0.9234	0.8885
0.0072	15.0	6495	0.8939	0.8962
0.0068	16.0	6928	0.9207	0.8940
0.0045	17.0	7361	0.8769	0.8968
0.004	18.0	7794	0.9354	0.8946
0.0024	19.0	8227	0.9192	0.8968
0.0012	20.0	8660	0.8990	0.8984

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3