distilbert_sst2_padding10model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst2_padding10model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding10model

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: 0.8972
Accuracy: 0.9017

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	0.2551	0.9023
0.3447	2.0	866	0.3196	0.8979
0.1734	3.0	1299	0.3882	0.9001
0.0877	4.0	1732	0.4801	0.9050
0.0444	5.0	2165	0.6567	0.8918
0.0206	6.0	2598	0.6090	0.9023
0.0145	7.0	3031	0.6415	0.9028
0.0145	8.0	3464	0.7532	0.9023
0.0083	9.0	3897	0.6840	0.9116
0.0073	10.0	4330	0.8115	0.9001
0.0131	11.0	4763	0.7755	0.9017
0.0083	12.0	5196	0.7370	0.9083
0.0045	13.0	5629	0.8288	0.9066
0.0072	14.0	6062	0.8585	0.9017
0.0072	15.0	6495	0.8054	0.9028
0.0064	16.0	6928	0.8080	0.9039
0.0059	17.0	7361	0.8245	0.9050
0.0019	18.0	7794	0.9924	0.8940
0.001	19.0	8227	0.9138	0.8984
0.0016	20.0	8660	0.8972	0.9017

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3