metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_bert_imdb_padding40model
    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: 0.939

N_bert_imdb_padding40model

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: 0.6742
Accuracy: 0.939

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
0.2234	1.0	1563	0.2483	0.9251
0.1543	2.0	3126	0.2148	0.9323
0.0957	3.0	4689	0.2969	0.9329
0.0674	4.0	6252	0.3085	0.9369
0.035	5.0	7815	0.3765	0.9367
0.0398	6.0	9378	0.4149	0.9368
0.0215	7.0	10941	0.4424	0.9376
0.0162	8.0	12504	0.4885	0.9352
0.0113	9.0	14067	0.4668	0.935
0.0168	10.0	15630	0.5267	0.9367
0.0077	11.0	17193	0.5049	0.9378
0.0082	12.0	18756	0.5595	0.9374
0.0055	13.0	20319	0.5650	0.9341
0.0035	14.0	21882	0.6518	0.9356
0.0017	15.0	23445	0.6662	0.9385
0.0036	16.0	25008	0.6536	0.9369
0.0	17.0	26571	0.7483	0.9354
0.0003	18.0	28134	0.7027	0.9368
0.0034	19.0	29697	0.6818	0.9384
0.0008	20.0	31260	0.6742	0.939

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3