metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_bert_imdb_padding30model
    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: 0.93944

N_bert_imdb_padding30model

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: 0.6907
Accuracy: 0.9394

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
0.2178	1.0	1563	0.2389	0.9234
0.1617	2.0	3126	0.2474	0.9303
0.0872	3.0	4689	0.3029	0.9283
0.065	4.0	6252	0.3493	0.9316
0.0348	5.0	7815	0.3685	0.9365
0.0311	6.0	9378	0.4913	0.9310
0.0205	7.0	10941	0.4485	0.9362
0.0177	8.0	12504	0.4903	0.9354
0.0147	9.0	14067	0.5786	0.9322
0.0119	10.0	15630	0.5245	0.9356
0.01	11.0	17193	0.5730	0.9364
0.0091	12.0	18756	0.5730	0.9383
0.006	13.0	20319	0.5596	0.9386
0.004	14.0	21882	0.6760	0.9354
0.0018	15.0	23445	0.5813	0.9402
0.0018	16.0	25008	0.6526	0.9378
0.0035	17.0	26571	0.6453	0.9384
0.0002	18.0	28134	0.6714	0.9392
0.0001	19.0	29697	0.6893	0.9397
0.0	20.0	31260	0.6907	0.9394

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3