distilbert_sst2_padding60model – AI Model by Realgon | AlphaNeural AI | AlphaNeural AI

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Realgon/
distilbert_sst2_padding60model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst2_padding60model

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: 0.8463
Accuracy: 0.9083

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	0.2875	0.8803
0.388	2.0	866	0.3043	0.8907
0.2044	3.0	1299	0.4016	0.8902
0.103	4.0	1732	0.4731	0.9006
0.0553	5.0	2165	0.5760	0.8990
0.0328	6.0	2598	0.7112	0.8891
0.0198	7.0	3031	0.6813	0.9072
0.0198	8.0	3464	0.6863	0.9077
0.0155	9.0	3897	0.7397	0.8990
0.0132	10.0	4330	0.9001	0.8902
0.0091	11.0	4763	0.7295	0.9066
0.0065	12.0	5196	0.7631	0.9044
0.0106	13.0	5629	0.8739	0.8979
0.0039	14.0	6062	0.7804	0.9050
0.0039	15.0	6495	0.8326	0.9066
0.0071	16.0	6928	0.8924	0.8990
0.0043	17.0	7361	0.8991	0.9028
0.0052	18.0	7794	0.8528	0.9072
0.0025	19.0	8227	0.8650	0.9055
0.0021	20.0	8660	0.8463	0.9083

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3