N_distilbert_twitterfin_padding30model – AI Model by Realgon | AlphaNeural AI

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Realgon/
N_distilbert_twitterfin_padding30model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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N_distilbert_twitterfin_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: 1.0998
Accuracy: 0.8811

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
0.6419	1.0	597	0.3913	0.8526
0.3669	2.0	1194	0.3503	0.8719
0.2631	3.0	1791	0.3806	0.8882
0.1808	4.0	2388	0.4746	0.8836
0.135	5.0	2985	0.6484	0.8748
0.0563	6.0	3582	0.6781	0.8777
0.0445	7.0	4179	0.7460	0.8815
0.0323	8.0	4776	0.7792	0.8777
0.0323	9.0	5373	0.8680	0.8740
0.0221	10.0	5970	0.8690	0.8811
0.0164	11.0	6567	0.9499	0.8769
0.0092	12.0	7164	0.9945	0.8752
0.0121	13.0	7761	0.9914	0.8802
0.0072	14.0	8358	1.0079	0.8819
0.0075	15.0	8955	1.0475	0.8790
0.0069	16.0	9552	1.0287	0.8827
0.0034	17.0	10149	1.0776	0.8823
0.0029	18.0	10746	1.1006	0.8815
0.0036	19.0	11343	1.0892	0.8811
0.0032	20.0	11940	1.0998	0.8811

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3