metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_distilbert_imdb_padding50model
    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: 0.93268

N_distilbert_imdb_padding50model

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: 0.7391
Accuracy: 0.9327

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
0.2431	1.0	1563	0.2690	0.9089
0.1734	2.0	3126	0.2418	0.9260
0.1167	3.0	4689	0.4345	0.9078
0.0685	4.0	6252	0.3717	0.926
0.0445	5.0	7815	0.4502	0.9242
0.0338	6.0	9378	0.4786	0.9287
0.0293	7.0	10941	0.5332	0.9214
0.0191	8.0	12504	0.5435	0.9287
0.0182	9.0	14067	0.5450	0.9265
0.015	10.0	15630	0.5398	0.9297
0.0122	11.0	17193	0.6565	0.9226
0.0089	12.0	18756	0.6521	0.9280
0.0081	13.0	20319	0.6755	0.9285
0.0067	14.0	21882	0.6753	0.93
0.0054	15.0	23445	0.7014	0.9305
0.0023	16.0	25008	0.7440	0.9308
0.0004	17.0	26571	0.7371	0.9286
0.0	18.0	28134	0.7497	0.9302
0.0004	19.0	29697	0.7386	0.9324
0.0002	20.0	31260	0.7391	0.9327

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3