metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_imdb_padding60model
    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: 0.95004

N_roberta_imdb_padding60model

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

Loss: 0.4811
Accuracy: 0.9500

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
0.2157	1.0	1563	0.2020	0.9366
0.1716	2.0	3126	0.1757	0.9467
0.1135	3.0	4689	0.2601	0.9442
0.0834	4.0	6252	0.2498	0.9485
0.0533	5.0	7815	0.3480	0.9452
0.0441	6.0	9378	0.3548	0.9371
0.0319	7.0	10941	0.3257	0.9474
0.0264	8.0	12504	0.3932	0.9457
0.0239	9.0	14067	0.3367	0.9469
0.0185	10.0	15630	0.4500	0.94
0.018	11.0	17193	0.3871	0.9470
0.0153	12.0	18756	0.4206	0.9456
0.0101	13.0	20319	0.4027	0.9492
0.005	14.0	21882	0.4701	0.9477
0.0051	15.0	23445	0.4454	0.9484
0.0013	16.0	25008	0.5015	0.9493
0.007	17.0	26571	0.5011	0.9476
0.0022	18.0	28134	0.4798	0.95
0.0047	19.0	29697	0.4794	0.9498
0.0014	20.0	31260	0.4811	0.9500

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3