distilbert-base-uncased-finetuned-emotion – AI Model by kiki2013 | AlphaNeural AI

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kiki2013/
distilbert-base-uncased-finetuned-emotion

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text-classification

generated_from_trainer

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 the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.2274
Accuracy: 0.9335
F1: 0.9335

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
0.1747	1.0	250	0.1884	0.9295	0.9286
0.1219	2.0	500	0.1533	0.9345	0.9347
0.1014	3.0	750	0.1600	0.932	0.9324
0.081	4.0	1000	0.1592	0.9365	0.9367
0.065	5.0	1250	0.1787	0.935	0.9347
0.0511	6.0	1500	0.1874	0.934	0.9339
0.0419	7.0	1750	0.2131	0.935	0.9353
0.0351	8.0	2000	0.2151	0.934	0.9344
0.0292	9.0	2250	0.2269	0.933	0.9332
0.024	10.0	2500	0.2274	0.9335	0.9335

Framework versions

Transformers 4.27.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2