metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: distilbert_imdb_padding90model
    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: 0.93092

distilbert_imdb_padding90model

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: 0.7443
Accuracy: 0.9309

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
0.2395	1.0	1563	0.2329	0.9140
0.1704	2.0	3126	0.2702	0.9175
0.1157	3.0	4689	0.3082	0.9254
0.0725	4.0	6252	0.3575	0.9204
0.049	5.0	7815	0.4781	0.9152
0.0379	6.0	9378	0.4916	0.9257
0.0236	7.0	10941	0.5292	0.9244
0.0248	8.0	12504	0.5522	0.9249
0.0198	9.0	14067	0.5522	0.9273
0.018	10.0	15630	0.5759	0.9286
0.0126	11.0	17193	0.6480	0.9268
0.0061	12.0	18756	0.6711	0.9295
0.0091	13.0	20319	0.6219	0.9293
0.0049	14.0	21882	0.7301	0.9261
0.0085	15.0	23445	0.6748	0.9299
0.0039	16.0	25008	0.6808	0.9306
0.003	17.0	26571	0.7055	0.9289
0.0037	18.0	28134	0.7126	0.9292
0.0	19.0	29697	0.7484	0.9295
0.001	20.0	31260	0.7443	0.9309

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3