metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: distilbert_imdb_padding20model
    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: 0.93304

distilbert_imdb_padding20model

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: 0.7052
Accuracy: 0.9330

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
0.2371	1.0	1563	0.2108	0.9213
0.1697	2.0	3126	0.2468	0.9285
0.1016	3.0	4689	0.3128	0.9250
0.0707	4.0	6252	0.3839	0.9192
0.0425	5.0	7815	0.4262	0.9238
0.033	6.0	9378	0.4711	0.9281
0.0226	7.0	10941	0.5034	0.9261
0.0274	8.0	12504	0.5279	0.9283
0.0092	9.0	14067	0.6002	0.9260
0.0099	10.0	15630	0.5944	0.9295
0.0035	11.0	17193	0.7042	0.9279
0.0119	12.0	18756	0.5989	0.9282
0.0068	13.0	20319	0.6468	0.9283
0.006	14.0	21882	0.6569	0.9307
0.0045	15.0	23445	0.7417	0.9299
0.0051	16.0	25008	0.6578	0.9322
0.0039	17.0	26571	0.6388	0.9325
0.0011	18.0	28134	0.6771	0.9324
0.0	19.0	29697	0.6996	0.9329
0.0017	20.0	31260	0.7052	0.9330

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3