metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_imdb_padding10model
    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: 0.95244

N_roberta_imdb_padding10model

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

Loss: 0.5407
Accuracy: 0.9524

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
0.2113	1.0	1563	0.2381	0.9337
0.1641	2.0	3126	0.1671	0.9498
0.1084	3.0	4689	0.2624	0.9476
0.0731	4.0	6252	0.2613	0.9496
0.0488	5.0	7815	0.3130	0.9481
0.0398	6.0	9378	0.3571	0.9473
0.0254	7.0	10941	0.3278	0.9494
0.0282	8.0	12504	0.4027	0.9466
0.0214	9.0	14067	0.3643	0.9493
0.0151	10.0	15630	0.4171	0.9495
0.0146	11.0	17193	0.4385	0.9505
0.0075	12.0	18756	0.4331	0.9523
0.0133	13.0	20319	0.3997	0.952
0.0053	14.0	21882	0.4604	0.9530
0.0044	15.0	23445	0.4686	0.952
0.0003	16.0	25008	0.5177	0.9508
0.0028	17.0	26571	0.5353	0.9514
0.0012	18.0	28134	0.5197	0.9525
0.0001	19.0	29697	0.5354	0.9519
0.0006	20.0	31260	0.5407	0.9524

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3