distilbert-base-uncased-finetuned-emotion-overall-2nd – AI Model by LeBruse | AlphaNeural AI

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LeBruse/
distilbert-base-uncased-finetuned-emotion-overall-2nd

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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-overall-2nd

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9642
Accuracy: 0.7753
F1: 0.7701

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
0.4263	1.0	63	0.7986	0.7654	0.7553
0.3167	2.0	126	0.8225	0.7674	0.7594
0.2212	3.0	189	0.8309	0.7734	0.7659
0.169	4.0	252	0.8867	0.7654	0.7597
0.1394	5.0	315	0.9140	0.7664	0.7607
0.1164	6.0	378	0.9379	0.7724	0.7677
0.0913	7.0	441	0.9397	0.7783	0.7732
0.0777	8.0	504	0.9515	0.7744	0.7694
0.0732	9.0	567	0.9616	0.7744	0.7692
0.0607	10.0	630	0.9642	0.7753	0.7701

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2