metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_distilbert_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: 0.9448684210526316

N_distilbert_agnews_padding40model

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

Loss: 0.6441
Accuracy: 0.9449

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
0.181	1.0	7500	0.1943	0.9399
0.1378	2.0	15000	0.2044	0.9443
0.1183	3.0	22500	0.2246	0.9459
0.088	4.0	30000	0.2517	0.9445
0.0614	5.0	37500	0.3074	0.9382
0.0464	6.0	45000	0.3765	0.9407
0.0368	7.0	52500	0.4057	0.9416
0.0245	8.0	60000	0.4436	0.9430
0.0202	9.0	67500	0.4608	0.9420
0.0119	10.0	75000	0.4479	0.9425
0.0125	11.0	82500	0.5133	0.9436
0.0147	12.0	90000	0.5036	0.9451
0.0103	13.0	97500	0.5727	0.9437
0.0051	14.0	105000	0.5684	0.9430
0.0056	15.0	112500	0.5746	0.9424
0.0031	16.0	120000	0.6067	0.9436
0.0009	17.0	127500	0.5994	0.9455
0.0025	18.0	135000	0.6187	0.9433
0.0024	19.0	142500	0.6413	0.9449
0.0011	20.0	150000	0.6441	0.9449

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3