metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: 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: 0.9468421052631579

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: 0.6171
Accuracy: 0.9468

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
0.1804	1.0	7500	0.1955	0.9395
0.1406	2.0	15000	0.1970	0.9429
0.1206	3.0	22500	0.2108	0.9467
0.0878	4.0	30000	0.2626	0.9429
0.0605	5.0	37500	0.3047	0.9417
0.0472	6.0	45000	0.3698	0.9397
0.0331	7.0	52500	0.4269	0.9367
0.0251	8.0	60000	0.4326	0.9416
0.0247	9.0	67500	0.4525	0.9428
0.0151	10.0	75000	0.4580	0.9462
0.0164	11.0	82500	0.5027	0.9455
0.0074	12.0	90000	0.5040	0.9437
0.0054	13.0	97500	0.5347	0.9449
0.0031	14.0	105000	0.5753	0.9451
0.0065	15.0	112500	0.5445	0.9453
0.0012	16.0	120000	0.5966	0.9461
0.0028	17.0	127500	0.5994	0.9445
0.0006	18.0	135000	0.5948	0.9455
0.0002	19.0	142500	0.6115	0.9471
0.0008	20.0	150000	0.6171	0.9468

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3