metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_bert_agnews_padding40model
    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: 0.9473684210526315

N_bert_agnews_padding40model

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

Loss: 0.5661
Accuracy: 0.9474

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
0.1785	1.0	7500	0.1884	0.9421
0.1379	2.0	15000	0.1990	0.9478
0.1127	3.0	22500	0.2389	0.9408
0.0846	4.0	30000	0.2528	0.9492
0.0581	5.0	37500	0.3041	0.9436
0.0456	6.0	45000	0.3415	0.9468
0.0411	7.0	52500	0.4081	0.9430
0.0239	8.0	60000	0.4415	0.9433
0.0202	9.0	67500	0.4380	0.9404
0.0126	10.0	75000	0.4637	0.9425
0.0175	11.0	82500	0.4485	0.9455
0.0126	12.0	90000	0.4761	0.9449
0.0046	13.0	97500	0.5009	0.9455
0.0038	14.0	105000	0.4784	0.9482
0.0035	15.0	112500	0.5282	0.9451
0.0046	16.0	120000	0.5256	0.9464
0.0026	17.0	127500	0.5081	0.9501
0.0008	18.0	135000	0.5543	0.9467
0.0002	19.0	142500	0.5448	0.9488
0.0016	20.0	150000	0.5661	0.9474

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3