N_distilbert_twitterfin_padding100model – AI Model by Realgon | AlphaNeural AI

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Realgon/
N_distilbert_twitterfin_padding100model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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N_distilbert_twitterfin_padding100model

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: 1.1124
Accuracy: 0.8760

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
0.6499	1.0	597	0.4008	0.8484
0.3558	2.0	1194	0.3977	0.8626
0.2591	3.0	1791	0.4112	0.8685
0.1811	4.0	2388	0.5229	0.8744
0.1298	5.0	2985	0.6057	0.8689
0.064	6.0	3582	0.6571	0.8685
0.0538	7.0	4179	0.7742	0.8681
0.0409	8.0	4776	0.8281	0.8706
0.0365	9.0	5373	0.8383	0.8723
0.0318	10.0	5970	0.8549	0.8752
0.0215	11.0	6567	0.9141	0.8756
0.0132	12.0	7164	0.9676	0.8735
0.0194	13.0	7761	1.0010	0.8740
0.0124	14.0	8358	1.0216	0.8765
0.0055	15.0	8955	1.0512	0.8719
0.0069	16.0	9552	1.0631	0.8781
0.0061	17.0	10149	1.1174	0.8740
0.0044	18.0	10746	1.0963	0.8794
0.0035	19.0	11343	1.1088	0.8744
0.0032	20.0	11940	1.1124	0.8760

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3