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_padding80model
    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: 0.9467105263157894

N_distilbert_agnews_padding80model

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: 0.6373
Accuracy: 0.9467

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
0.1867	1.0	7500	0.1871	0.9422
0.1412	2.0	15000	0.1944	0.9457
0.1163	3.0	22500	0.2140	0.945
0.0838	4.0	30000	0.2455	0.9476
0.0572	5.0	37500	0.2839	0.9436
0.0433	6.0	45000	0.3780	0.9411
0.035	7.0	52500	0.4167	0.9384
0.0303	8.0	60000	0.4762	0.9401
0.0198	9.0	67500	0.4682	0.9407
0.0186	10.0	75000	0.4855	0.9429
0.0166	11.0	82500	0.5062	0.9416
0.0125	12.0	90000	0.5277	0.9418
0.0061	13.0	97500	0.5436	0.9442
0.0028	14.0	105000	0.5485	0.9420
0.0034	15.0	112500	0.5601	0.9441
0.0029	16.0	120000	0.5588	0.9459
0.0032	17.0	127500	0.6078	0.9436
0.0046	18.0	135000	0.6353	0.9429
0.0003	19.0	142500	0.6454	0.9458
0.0011	20.0	150000	0.6373	0.9467

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3