metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding90model
    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: 0.9443421052631579

distilbert_agnews_padding90model

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: 0.6543
Accuracy: 0.9443

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
0.1824	1.0	7500	0.1893	0.9428
0.1381	2.0	15000	0.2112	0.9401
0.1208	3.0	22500	0.2110	0.9449
0.091	4.0	30000	0.2609	0.9428
0.065	5.0	37500	0.2991	0.9417
0.0447	6.0	45000	0.3947	0.9408
0.0374	7.0	52500	0.4052	0.9354
0.0275	8.0	60000	0.4441	0.9418
0.0198	9.0	67500	0.4479	0.9408
0.0131	10.0	75000	0.5038	0.9387
0.0128	11.0	82500	0.5114	0.9424
0.0098	12.0	90000	0.5130	0.9436
0.0085	13.0	97500	0.5473	0.9414
0.0066	14.0	105000	0.5601	0.9429
0.0054	15.0	112500	0.5617	0.9424
0.0023	16.0	120000	0.5911	0.9433
0.0021	17.0	127500	0.6165	0.9442
0.0038	18.0	135000	0.6105	0.9446
0.0008	19.0	142500	0.6462	0.9422
0.0004	20.0	150000	0.6543	0.9443

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3