metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_distilbert_imdb_padding100model
    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: 0.92944

N_distilbert_imdb_padding100model

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: 0.7393
Accuracy: 0.9294

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
0.2387	1.0	1563	0.2354	0.919
0.1866	2.0	3126	0.2345	0.9248
0.1194	3.0	4689	0.3117	0.9212
0.0615	4.0	6252	0.3370	0.9219
0.0475	5.0	7815	0.5367	0.9131
0.0394	6.0	9378	0.5018	0.9236
0.0281	7.0	10941	0.5039	0.9243
0.0262	8.0	12504	0.5149	0.9238
0.0203	9.0	14067	0.5159	0.9275
0.0194	10.0	15630	0.5855	0.927
0.0092	11.0	17193	0.6452	0.9259
0.0097	12.0	18756	0.6318	0.9262
0.0024	13.0	20319	0.6537	0.9292
0.0056	14.0	21882	0.7551	0.9268
0.0037	15.0	23445	0.7516	0.9255
0.0073	16.0	25008	0.7335	0.9281
0.0025	17.0	26571	0.6959	0.9301
0.0008	18.0	28134	0.7439	0.9276
0.0005	19.0	29697	0.7300	0.9296
0.0004	20.0	31260	0.7393	0.9294

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3