metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_bert_imdb_padding0model
    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: 0.94052

N_bert_imdb_padding0model

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: 0.6575
Accuracy: 0.9405

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
0.2204	1.0	1563	0.2086	0.9332
0.1501	2.0	3126	0.2195	0.9356
0.0871	3.0	4689	0.3156	0.935
0.0555	4.0	6252	0.3170	0.9314
0.0362	5.0	7815	0.3568	0.9353
0.0282	6.0	9378	0.4438	0.9380
0.0199	7.0	10941	0.4900	0.9357
0.0219	8.0	12504	0.4963	0.9344
0.0115	9.0	14067	0.5554	0.9333
0.0078	10.0	15630	0.5974	0.9340
0.0087	11.0	17193	0.6081	0.9360
0.0038	12.0	18756	0.5909	0.9322
0.0096	13.0	20319	0.6002	0.9381
0.0061	14.0	21882	0.5645	0.9372
0.0057	15.0	23445	0.6415	0.9388
0.0019	16.0	25008	0.6901	0.9388
0.0005	17.0	26571	0.7099	0.9389
0.0	18.0	28134	0.7022	0.9392
0.0008	19.0	29697	0.6640	0.9398
0.0	20.0	31260	0.6575	0.9405

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3