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_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: 0.9473684210526315

N_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: 0.6235
Accuracy: 0.9474

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
0.1806	1.0	7500	0.1897	0.9411
0.1426	2.0	15000	0.2027	0.9421
0.1169	3.0	22500	0.2151	0.9447
0.0978	4.0	30000	0.2648	0.9421
0.0634	5.0	37500	0.3140	0.9393
0.0385	6.0	45000	0.3887	0.9413
0.0335	7.0	52500	0.4336	0.9378
0.0317	8.0	60000	0.4547	0.9405
0.0192	9.0	67500	0.4665	0.9389
0.0091	10.0	75000	0.4814	0.9422
0.0142	11.0	82500	0.5405	0.9422
0.0131	12.0	90000	0.5560	0.9416
0.0131	13.0	97500	0.5343	0.9413
0.005	14.0	105000	0.5242	0.9430
0.0013	15.0	112500	0.5975	0.9425
0.003	16.0	120000	0.5905	0.9430
0.0024	17.0	127500	0.5740	0.9453
0.0009	18.0	135000	0.6001	0.9457
0.0012	19.0	142500	0.6177	0.9467
0.0002	20.0	150000	0.6235	0.9474

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3