roberta_sst2_padding30model – AI Model by Realgon | AlphaNeural AI

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Realgon/
roberta_sst2_padding30model

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta_sst2_padding30model

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5215
Accuracy: 0.9412

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	433	0.1665	0.9396
0.3401	2.0	866	0.1830	0.9368
0.1936	3.0	1299	0.4096	0.9138
0.1178	4.0	1732	0.3273	0.9412
0.0709	5.0	2165	0.4273	0.9325
0.0501	6.0	2598	0.4050	0.9341
0.0317	7.0	3031	0.4084	0.9401
0.0317	8.0	3464	0.4631	0.9379
0.0124	9.0	3897	0.6065	0.9209
0.0216	10.0	4330	0.5480	0.9275
0.0148	11.0	4763	0.4557	0.9401
0.0141	12.0	5196	0.4668	0.9418
0.0122	13.0	5629	0.5264	0.9347
0.0114	14.0	6062	0.5080	0.9429
0.0114	15.0	6495	0.5438	0.9390
0.0108	16.0	6928	0.5652	0.9363
0.007	17.0	7361	0.4768	0.9445
0.0044	18.0	7794	0.5182	0.9423
0.0029	19.0	8227	0.5217	0.9407
0.0022	20.0	8660	0.5215	0.9412

Framework versions

Transformers 4.32.1
Pytorch 2.1.1
Datasets 2.12.0
Tokenizers 0.13.3