distilbert-finetuning – AI Model by theunmans | AlphaNeural AI

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theunmans/
distilbert-finetuning

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distilbert/distilbert-base-uncased

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distilbert-finetuning

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: 0.7899
Accuracy: 0.8078
F1: 0.8069

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6237	1.0	65741	0.8881	0.7796	0.7739
1.3107	2.0	131482	0.8164	0.7995	0.7953
0.8264	3.0	197223	0.7899	0.8078	0.8069
0.4175	4.0	262964	0.8556	0.8130	0.8116
0.3076	5.0	328705	0.9789	0.8127	0.8116

Framework versions

Transformers 4.43.3
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1