metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_bert_imdb_padding10model
    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: 0.93976

N_bert_imdb_padding10model

This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

Loss: 0.6695
Accuracy: 0.9398

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
0.2175	1.0	1563	0.2147	0.9269
0.1483	2.0	3126	0.2123	0.9384
0.0912	3.0	4689	0.2707	0.9325
0.0569	4.0	6252	0.3262	0.9314
0.042	5.0	7815	0.3316	0.9372
0.0373	6.0	9378	0.4147	0.9365
0.0181	7.0	10941	0.4632	0.936
0.0144	8.0	12504	0.5192	0.9338
0.0138	9.0	14067	0.4934	0.9388
0.0094	10.0	15630	0.5627	0.9363
0.0091	11.0	17193	0.6356	0.9285
0.0114	12.0	18756	0.5780	0.9368
0.0025	13.0	20319	0.6362	0.9402
0.0067	14.0	21882	0.5902	0.9388
0.0043	15.0	23445	0.6124	0.9387
0.0029	16.0	25008	0.5929	0.9380
0.0001	17.0	26571	0.6554	0.9394
0.0005	18.0	28134	0.6619	0.9408
0.0019	19.0	29697	0.6654	0.9398
0.0	20.0	31260	0.6695	0.9398

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3