metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: distilbert_imdb_padding60model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: imdb
          type: imdb
          config: plain_text
          split: test
          args: plain_text
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9334

distilbert_imdb_padding60model

This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

Loss: 0.7595
Accuracy: 0.9334

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
0.2373	1.0	1563	0.2252	0.9165
0.1765	2.0	3126	0.2079	0.9274
0.1139	3.0	4689	0.2956	0.9302
0.0677	4.0	6252	0.3145	0.9261
0.0337	5.0	7815	0.4048	0.9280
0.0359	6.0	9378	0.4836	0.9296
0.0229	7.0	10941	0.5211	0.9228
0.0203	8.0	12504	0.5524	0.9280
0.015	9.0	14067	0.5274	0.9291
0.0214	10.0	15630	0.5787	0.9266
0.0134	11.0	17193	0.5935	0.9299
0.0075	12.0	18756	0.6236	0.9306
0.0054	13.0	20319	0.6758	0.9279
0.0057	14.0	21882	0.6801	0.9301
0.0066	15.0	23445	0.7197	0.929
0.0021	16.0	25008	0.7070	0.9321
0.0014	17.0	26571	0.6949	0.9320
0.0001	18.0	28134	0.7482	0.9319
0.0014	19.0	29697	0.7587	0.9334
0.0004	20.0	31260	0.7595	0.9334

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3