distilbert_sst2_padding70model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst2_padding70model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding70model

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: 0.8873
Accuracy: 0.9039

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	0.2844	0.8902
0.3687	2.0	866	0.3666	0.8819
0.1942	3.0	1299	0.3832	0.8968
0.0897	4.0	1732	0.5142	0.9012
0.0536	5.0	2165	0.5252	0.9028
0.0318	6.0	2598	0.6097	0.9001
0.0167	7.0	3031	0.7827	0.8858
0.0167	8.0	3464	0.7161	0.9044
0.0068	9.0	3897	0.7272	0.9072
0.012	10.0	4330	0.7150	0.9094
0.0076	11.0	4763	0.7475	0.9083
0.0098	12.0	5196	0.7788	0.9023
0.0108	13.0	5629	0.8121	0.9039
0.0051	14.0	6062	0.8801	0.8995
0.0051	15.0	6495	0.9357	0.8957
0.0089	16.0	6928	0.8661	0.8979
0.0036	17.0	7361	0.7991	0.9088
0.0027	18.0	7794	0.9503	0.8968
0.0013	19.0	8227	0.8711	0.9044
0.0011	20.0	8660	0.8873	0.9039

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3