README.md

metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_roberta_agnews_padding50model
    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_padding50model

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: 0.5524
• 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
0.1998	1.0	7500	0.2132	0.9382
0.1682	2.0	15000	0.2009	0.9475
0.1506	3.0	22500	0.2273	0.9446
0.1294	4.0	30000	0.2495	0.9482
0.1028	5.0	37500	0.2612	0.9459
0.0797	6.0	45000	0.2966	0.9457
0.0646	7.0	52500	0.3040	0.9458
0.0531	8.0	60000	0.3825	0.9446
0.0443	9.0	67500	0.3838	0.9425
0.0345	10.0	75000	0.3968	0.9475
0.0395	11.0	82500	0.4132	0.9474
0.019	12.0	90000	0.4612	0.9453
0.0219	13.0	97500	0.4559	0.9458
0.0067	14.0	105000	0.4692	0.9467
0.0065	15.0	112500	0.5118	0.9461
0.0045	16.0	120000	0.5115	0.9470
0.004	17.0	127500	0.5326	0.9472
0.0079	18.0	135000	0.5088	0.9483
0.0039	19.0	142500	0.5359	0.9504
0.0024	20.0	150000	0.5524	0.9486

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.13.3