roberta-base-finetuned-sdg – AI Model by jonas | AlphaNeural AI

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roberta-base-finetuned-sdg

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-base-finetuned-sdg

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

Loss: 0.4993
Acc: 0.9024

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: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Acc
0.4679	1.0	254	0.3660	0.8963
0.3578	2.0	508	0.3689	0.9019
0.2739	3.0	762	0.3284	0.9035
0.1841	4.0	1016	0.3763	0.9019
0.1127	5.0	1270	0.4174	0.9024
0.0822	6.0	1524	0.4523	0.9013
0.0329	7.0	1778	0.4829	0.9030
0.0157	8.0	2032	0.4993	0.9024

Framework versions

Transformers 4.21.1
Pytorch 1.12.0a0+8a1a93a
Datasets 2.4.0
Tokenizers 0.12.1