distilbert-base-uncased-finetuned-emotion – AI Model by moraudiet | AlphaNeural AI

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moraudiet/
distilbert-base-uncased-finetuned-emotion

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-emotion

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: 0.1769
Accuracy: 0.942
F1: 0.9421

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8137	1.0	250	0.2667	0.9155	0.9156
0.202	2.0	500	0.1705	0.9315	0.9310
0.1316	3.0	750	0.1430	0.941	0.9416
0.1029	4.0	1000	0.1459	0.939	0.9389
0.0835	5.0	1250	0.1527	0.937	0.9366
0.0694	6.0	1500	0.1581	0.9375	0.9374
0.0577	7.0	1750	0.1686	0.9375	0.9374
0.0484	8.0	2000	0.1681	0.942	0.9420
0.0393	9.0	2250	0.1738	0.9425	0.9425
0.0355	10.0	2500	0.1769	0.942	0.9421

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.2
Tokenizers 0.19.1