roberta-mc-2 – AI Model by bimoadiparwa | AlphaNeural AI

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bimoadiparwa/
roberta-mc-2

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roberta-mc-2

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

Loss: 1.5972
Accuracy: 0.4

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-06
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6096	1.0	24	1.6086	0.3
1.614	2.0	48	1.6083	0.4
1.6032	3.0	72	1.6070	0.4
1.6185	4.0	96	1.6057	0.4
1.6106	5.0	120	1.6045	0.4
1.6093	6.0	144	1.6028	0.4
1.597	7.0	168	1.6010	0.4
1.6094	8.0	192	1.5994	0.4
1.6029	9.0	216	1.5977	0.4
1.5997	10.0	240	1.5972	0.4

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3