metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_roberta_agnews_padding10model
    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: 0.9506578947368421

N_roberta_agnews_padding10model

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: 0.5342
Accuracy: 0.9507

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
0.1973	1.0	7500	0.2025	0.9403
0.1674	2.0	15000	0.1876	0.9471
0.1488	3.0	22500	0.2367	0.9446
0.1213	4.0	30000	0.2451	0.9461
0.0942	5.0	37500	0.2545	0.9464
0.0842	6.0	45000	0.3061	0.9446
0.0718	7.0	52500	0.2821	0.9476
0.0562	8.0	60000	0.4124	0.9443
0.0387	9.0	67500	0.4309	0.9409
0.0299	10.0	75000	0.4162	0.9470
0.028	11.0	82500	0.4086	0.9479
0.026	12.0	90000	0.4091	0.9466
0.0205	13.0	97500	0.4481	0.9457
0.0124	14.0	105000	0.4895	0.9453
0.0093	15.0	112500	0.5086	0.9463
0.0075	16.0	120000	0.4911	0.9487
0.0068	17.0	127500	0.4924	0.9496
0.0023	18.0	135000	0.5008	0.9503
0.0014	19.0	142500	0.5251	0.9505
0.0049	20.0	150000	0.5342	0.9507

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3