metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: distilbert_imdb_padding0model
    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: 0.9328

distilbert_imdb_padding0model

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: 0.7541
Accuracy: 0.9328

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
0.2321	1.0	1563	0.2211	0.9195
0.1748	2.0	3126	0.2320	0.9289
0.1084	3.0	4689	0.3254	0.9251
0.0715	4.0	6252	0.3303	0.9267
0.0433	5.0	7815	0.4353	0.9276
0.0335	6.0	9378	0.4458	0.9302
0.033	7.0	10941	0.4704	0.9282
0.0171	8.0	12504	0.5326	0.9281
0.0147	9.0	14067	0.5456	0.9292
0.0099	10.0	15630	0.6037	0.9274
0.0166	11.0	17193	0.5636	0.9286
0.0101	12.0	18756	0.6355	0.9276
0.0086	13.0	20319	0.6102	0.9288
0.0068	14.0	21882	0.6305	0.9331
0.005	15.0	23445	0.6391	0.9293
0.0009	16.0	25008	0.7000	0.9339
0.0035	17.0	26571	0.7205	0.9325
0.0017	18.0	28134	0.7649	0.9294
0.0007	19.0	29697	0.7745	0.9329
0.0023	20.0	31260	0.7541	0.9328

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3