metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: distilbert_imdb_padding80model
    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: 0.92892

distilbert_imdb_padding80model

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: 0.7659
Accuracy: 0.9289

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
0.2429	1.0	1563	0.2099	0.923
0.1777	2.0	3126	0.2439	0.9231
0.116	3.0	4689	0.3167	0.9248
0.0668	4.0	6252	0.3296	0.9229
0.0448	5.0	7815	0.4632	0.9216
0.0326	6.0	9378	0.5330	0.9122
0.0275	7.0	10941	0.5065	0.9242
0.0187	8.0	12504	0.5384	0.9238
0.0225	9.0	14067	0.4589	0.9260
0.0069	10.0	15630	0.6072	0.9269
0.0176	11.0	17193	0.5474	0.9269
0.0106	12.0	18756	0.6218	0.9272
0.0068	13.0	20319	0.6779	0.9263
0.0068	14.0	21882	0.6249	0.9263
0.0005	15.0	23445	0.6835	0.929
0.0014	16.0	25008	0.7223	0.929
0.002	17.0	26571	0.7401	0.9281
0.0011	18.0	28134	0.7324	0.9293
0.0	19.0	29697	0.7678	0.9289
0.0002	20.0	31260	0.7659	0.9289

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3