metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding20model
    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: 0.9452631578947368

distilbert_agnews_padding20model

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: 0.6477
Accuracy: 0.9453

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
0.18	1.0	7500	0.1831	0.9426
0.1365	2.0	15000	0.2039	0.9420
0.1176	3.0	22500	0.2202	0.9470
0.0899	4.0	30000	0.2601	0.9443
0.0547	5.0	37500	0.2919	0.9429
0.0387	6.0	45000	0.3618	0.9459
0.0351	7.0	52500	0.4129	0.9413
0.031	8.0	60000	0.4379	0.9436
0.0171	9.0	67500	0.4794	0.9429
0.0156	10.0	75000	0.4744	0.9438
0.0147	11.0	82500	0.4832	0.9457
0.0108	12.0	90000	0.5166	0.9447
0.0034	13.0	97500	0.5083	0.9459
0.0065	14.0	105000	0.5451	0.9446
0.0062	15.0	112500	0.5926	0.9443
0.0031	16.0	120000	0.6059	0.9433
0.001	17.0	127500	0.6312	0.9463
0.0004	18.0	135000	0.6197	0.9454
0.0004	19.0	142500	0.6472	0.9455
0.0002	20.0	150000	0.6477	0.9453

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3