distilbert_sst2_padding30model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst2_padding30model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding30model

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: 0.9632
Accuracy: 0.9006

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	0.2757	0.8858
0.3485	2.0	866	0.3100	0.8984
0.1782	3.0	1299	0.4273	0.8935
0.0895	4.0	1732	0.4325	0.9066
0.0512	5.0	2165	0.6135	0.8918
0.0236	6.0	2598	0.6313	0.9006
0.02	7.0	3031	0.7291	0.8962
0.02	8.0	3464	0.6923	0.9017
0.0115	9.0	3897	0.8131	0.8968
0.0097	10.0	4330	0.8803	0.8957
0.0065	11.0	4763	0.7678	0.9066
0.0042	12.0	5196	0.7838	0.8995
0.0079	13.0	5629	0.9639	0.8918
0.0029	14.0	6062	0.8444	0.9050
0.0029	15.0	6495	0.8437	0.9039
0.0039	16.0	6928	0.8723	0.9072
0.0034	17.0	7361	0.9462	0.9012
0.0016	18.0	7794	0.8981	0.9039
0.0019	19.0	8227	0.9824	0.9006
0.0011	20.0	8660	0.9632	0.9006

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3