metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_distilbert_imdb_padding30model
    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: 0.93196

N_distilbert_imdb_padding30model

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: 0.7513
Accuracy: 0.9320

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
0.2412	1.0	1563	0.2749	0.9004
0.1694	2.0	3126	0.2355	0.9270
0.1055	3.0	4689	0.3029	0.9262
0.0621	4.0	6252	0.3240	0.9282
0.0422	5.0	7815	0.4462	0.9269
0.0366	6.0	9378	0.4963	0.9274
0.0309	7.0	10941	0.5017	0.9286
0.0189	8.0	12504	0.6588	0.9198
0.0217	9.0	14067	0.5946	0.9218
0.02	10.0	15630	0.6104	0.9248
0.0112	11.0	17193	0.5921	0.9293
0.0096	12.0	18756	0.6499	0.9290
0.0075	13.0	20319	0.6577	0.9299
0.0036	14.0	21882	0.6225	0.9289
0.0043	15.0	23445	0.6558	0.9290
0.0015	16.0	25008	0.6923	0.9314
0.0036	17.0	26571	0.7606	0.9284
0.0	18.0	28134	0.7696	0.931
0.0028	19.0	29697	0.7493	0.9319
0.0005	20.0	31260	0.7513	0.9320

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3