metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_bert_imdb_padding100model
    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: 0.93724

N_bert_imdb_padding100model

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: 0.7094
Accuracy: 0.9372

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
0.2271	1.0	1563	0.2627	0.9098
0.1657	2.0	3126	0.2289	0.9296
0.0928	3.0	4689	0.3241	0.9247
0.0656	4.0	6252	0.3616	0.9314
0.045	5.0	7815	0.3673	0.9310
0.034	6.0	9378	0.4597	0.9307
0.0202	7.0	10941	0.4430	0.9364
0.0188	8.0	12504	0.5484	0.9296
0.0144	9.0	14067	0.5043	0.9344
0.0115	10.0	15630	0.5540	0.9336
0.0094	11.0	17193	0.4962	0.9338
0.0066	12.0	18756	0.5736	0.9364
0.0068	13.0	20319	0.6779	0.9335
0.0038	14.0	21882	0.6431	0.9355
0.0021	15.0	23445	0.6151	0.9359
0.0009	16.0	25008	0.7113	0.9348
0.0	17.0	26571	0.7734	0.9336
0.003	18.0	28134	0.7006	0.9372
0.0008	19.0	29697	0.7140	0.9374
0.0	20.0	31260	0.7094	0.9372

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3