metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding70model
    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: 0.9439473684210526

distilbert_agnews_padding70model

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: 0.6779
Accuracy: 0.9439

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
0.1805	1.0	7500	0.1957	0.9380
0.1379	2.0	15000	0.1941	0.9458
0.1158	3.0	22500	0.2227	0.9455
0.0883	4.0	30000	0.2490	0.9426
0.067	5.0	37500	0.2904	0.9432
0.0453	6.0	45000	0.3748	0.9374
0.0432	7.0	52500	0.4024	0.9393
0.032	8.0	60000	0.4109	0.9437
0.0151	9.0	67500	0.4531	0.9425
0.0126	10.0	75000	0.4813	0.9418
0.0171	11.0	82500	0.5143	0.9424
0.0122	12.0	90000	0.5222	0.9412
0.0099	13.0	97500	0.5366	0.9438
0.008	14.0	105000	0.5356	0.9437
0.0066	15.0	112500	0.5689	0.9437
0.0026	16.0	120000	0.5860	0.9449
0.0031	17.0	127500	0.6363	0.9434
0.0017	18.0	135000	0.6474	0.9433
0.0007	19.0	142500	0.6755	0.9437
0.0008	20.0	150000	0.6779	0.9439

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3