metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_roberta_agnews_padding20model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9485526315789473

N_roberta_agnews_padding20model

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

Loss: 0.5475
Accuracy: 0.9486

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
0.1932	1.0	7500	0.1956	0.9442
0.1695	2.0	15000	0.1987	0.9459
0.1531	3.0	22500	0.2017	0.9462
0.1247	4.0	30000	0.2431	0.9479
0.1026	5.0	37500	0.2465	0.9479
0.078	6.0	45000	0.3001	0.9478
0.0752	7.0	52500	0.3209	0.945
0.048	8.0	60000	0.3456	0.9484
0.0408	9.0	67500	0.4119	0.9436
0.0338	10.0	75000	0.3976	0.945
0.0305	11.0	82500	0.4211	0.945
0.022	12.0	90000	0.4607	0.9470
0.0224	13.0	97500	0.4733	0.9464
0.0127	14.0	105000	0.4984	0.9466
0.0135	15.0	112500	0.4808	0.9492
0.0085	16.0	120000	0.4993	0.9497
0.0045	17.0	127500	0.5184	0.9475
0.0046	18.0	135000	0.5259	0.9479
0.0037	19.0	142500	0.5419	0.9483
0.0017	20.0	150000	0.5475	0.9486

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3