metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: 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: 0.93044

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: 0.7456
Accuracy: 0.9304

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
0.239	1.0	1563	0.2904	0.9081
0.1693	2.0	3126	0.2311	0.9272
0.1117	3.0	4689	0.3226	0.9248
0.0626	4.0	6252	0.3785	0.9226
0.0467	5.0	7815	0.4768	0.9175
0.0292	6.0	9378	0.4735	0.9241
0.0294	7.0	10941	0.5132	0.9261
0.0207	8.0	12504	0.5925	0.9162
0.0229	9.0	14067	0.5995	0.9240
0.0076	10.0	15630	0.6841	0.9224
0.0125	11.0	17193	0.6141	0.9272
0.0046	12.0	18756	0.6427	0.9293
0.007	13.0	20319	0.6095	0.9284
0.0051	14.0	21882	0.7158	0.9250
0.0037	15.0	23445	0.7008	0.9268
0.0023	16.0	25008	0.7489	0.9280
0.0023	17.0	26571	0.7541	0.9282
0.0001	18.0	28134	0.7298	0.9299
0.0013	19.0	29697	0.7388	0.9304
0.001	20.0	31260	0.7456	0.9304

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3