japanese-roberta-base-finetuned-rinna – AI Model by Bersk | AlphaNeural AI

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Bersk/
japanese-roberta-base-finetuned-rinna

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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japanese-roberta-base-finetuned-rinna

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

Loss: 0.9637
Precision: 0.8062
Recall: 0.8107
F1: 0.8071

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: 4
eval_batch_size: 4
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
0.7188	1.0	617	0.5825	0.7584	0.7945	0.7724
0.5951	2.0	1234	0.7466	0.7489	0.7799	0.7628
0.5206	3.0	1851	0.9570	0.7814	0.7767	0.7747
0.4061	4.0	2468	0.9637	0.8062	0.8107	0.8071
0.1879	5.0	3085	1.0516	0.8028	0.8026	0.8021

Framework versions

Transformers 4.25.1
Pytorch 1.13.0
Datasets 2.8.0
Tokenizers 0.13.2