metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_imdb_padding50model
    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: 0.95304

N_roberta_imdb_padding50model

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

Loss: 0.5385
Accuracy: 0.9530

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
0.2002	1.0	1563	0.2254	0.9357
0.1628	2.0	3126	0.1732	0.9478
0.115	3.0	4689	0.2905	0.9365
0.0737	4.0	6252	0.2347	0.9474
0.062	5.0	7815	0.3516	0.9472
0.0466	6.0	9378	0.3532	0.9452
0.0295	7.0	10941	0.3115	0.9481
0.0213	8.0	12504	0.4286	0.9479
0.0196	9.0	14067	0.4348	0.9483
0.019	10.0	15630	0.5160	0.9376
0.0177	11.0	17193	0.4682	0.9467
0.004	12.0	18756	0.4670	0.9503
0.0076	13.0	20319	0.4573	0.9501
0.0054	14.0	21882	0.5279	0.9504
0.0055	15.0	23445	0.4883	0.9504
0.0051	16.0	25008	0.4782	0.9525
0.0021	17.0	26571	0.4732	0.9527
0.0007	18.0	28134	0.5154	0.9519
0.0029	19.0	29697	0.5317	0.9524
0.002	20.0	31260	0.5385	0.9530

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3