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gabizh/
dbbuc_OG

Name: dbbuc_OG
Rating: 2.5 (5 reviews)

generated_from_trainer

distilbert/distilbert-base-uncased

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dbbuc_10p

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

Loss: 0.0645
Precision: 0.4907
Recall: 0.5
F1: 0.4953
Accuracy: 0.9658

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

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	205	0.0701	0.2691	0.2857	0.2771	0.9536
No log	2.0	410	0.0572	0.4673	0.4540	0.4605	0.9644
0.0685	3.0	615	0.0646	0.4848	0.4302	0.4558	0.9641
0.0685	4.0	820	0.0614	0.4740	0.5063	0.4896	0.9648
0.0184	5.0	1025	0.0645	0.4907	0.5	0.4953	0.9658

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

gabizh/dbbuc_OG

dbbuc_10p

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gabizh/
dbbuc_OG