roberta-base-finetuned-stationary – AI Model by Luggi | AlphaNeural AI

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Luggi/
roberta-base-finetuned-stationary

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta-base-finetuned-stationary

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

Loss: 0.8655
Accuracy: 0.8033
F1: 0.7996

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: 64
eval_batch_size: 64
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	F1
0.6155	1.0	38	0.4912	0.7333	0.7055
0.4549	2.0	76	0.4275	0.8067	0.8095
0.3466	3.0	114	0.4456	0.79	0.7908
0.2956	4.0	152	0.6039	0.7933	0.7731
0.2032	5.0	190	0.5564	0.8067	0.8020
0.1449	6.0	228	0.6809	0.8	0.7920
0.1124	7.0	266	0.7343	0.7967	0.7941
0.0725	8.0	304	0.8482	0.8033	0.7959
0.0682	9.0	342	0.8575	0.8067	0.8020
0.0521	10.0	380	0.8655	0.8033	0.7996

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0