distilbert_sst2_padding80model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst2_padding80model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding80model

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: 0.8177
Accuracy: 0.9105

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	0.2861	0.8819
0.3536	2.0	866	0.4254	0.8677
0.1914	3.0	1299	0.4265	0.8962
0.0987	4.0	1732	0.4661	0.9001
0.0533	5.0	2165	0.6232	0.9001
0.0231	6.0	2598	0.7215	0.8935
0.0291	7.0	3031	0.6435	0.9028
0.0291	8.0	3464	0.8011	0.8924
0.0168	9.0	3897	0.6787	0.9039
0.0155	10.0	4330	0.7006	0.9028
0.0094	11.0	4763	0.6975	0.9055
0.0103	12.0	5196	0.7654	0.9044
0.0074	13.0	5629	0.7544	0.9077
0.0061	14.0	6062	0.7732	0.9033
0.0061	15.0	6495	0.7836	0.9094
0.003	16.0	6928	0.9079	0.9028
0.0046	17.0	7361	0.8466	0.9055
0.0018	18.0	7794	0.8358	0.9044
0.004	19.0	8227	0.8357	0.9083
0.0016	20.0	8660	0.8177	0.9105

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3