N_distilbert_twitterfin_padding60model – AI Model by Realgon | AlphaNeural AI

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Realgon/
N_distilbert_twitterfin_padding60model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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N_distilbert_twitterfin_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: 1.1208
Accuracy: 0.8781

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
0.6919	1.0	597	0.4483	0.8275
0.4011	2.0	1194	0.3834	0.8647
0.2934	3.0	1791	0.4172	0.8786
0.2041	4.0	2388	0.5846	0.8714
0.153	5.0	2985	0.5842	0.8689
0.0739	6.0	3582	0.6274	0.8673
0.0669	7.0	4179	0.7207	0.8714
0.057	8.0	4776	0.7701	0.8639
0.0419	9.0	5373	0.8463	0.8673
0.0243	10.0	5970	0.9287	0.8706
0.0213	11.0	6567	0.9645	0.8681
0.0197	12.0	7164	1.0054	0.8748
0.0145	13.0	7761	1.0365	0.8706
0.0103	14.0	8358	1.0230	0.8731
0.0104	15.0	8955	1.0675	0.8740
0.0062	16.0	9552	1.1329	0.8706
0.0053	17.0	10149	1.1408	0.8760
0.0053	18.0	10746	1.1129	0.8773
0.0024	19.0	11343	1.1178	0.8752
0.0019	20.0	11940	1.1208	0.8781

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3