metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_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: 0.94952

N_roberta_imdb_padding40model

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

Loss: 0.4922
Accuracy: 0.9495

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
0.2081	1.0	1563	0.2432	0.9283
0.1726	2.0	3126	0.1724	0.9493
0.114	3.0	4689	0.2842	0.9384
0.0767	4.0	6252	0.2583	0.9463
0.0552	5.0	7815	0.3703	0.9420
0.0357	6.0	9378	0.3342	0.9386
0.0318	7.0	10941	0.3284	0.9462
0.0316	8.0	12504	0.4194	0.9410
0.0149	9.0	14067	0.4083	0.9483
0.0175	10.0	15630	0.4237	0.9468
0.0151	11.0	17193	0.4459	0.9457
0.0113	12.0	18756	0.4569	0.9478
0.0061	13.0	20319	0.4325	0.9482
0.0034	14.0	21882	0.5188	0.9472
0.0059	15.0	23445	0.4740	0.9484
0.0078	16.0	25008	0.4421	0.9485
0.0	17.0	26571	0.4819	0.9493
0.0035	18.0	28134	0.4845	0.9492
0.0	19.0	29697	0.5065	0.9486
0.0013	20.0	31260	0.4922	0.9495

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3