metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_imdb_padding20model
    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: 0.95256

N_roberta_imdb_padding20model

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

Loss: 0.5709
Accuracy: 0.9526

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
0.2052	1.0	1563	0.1966	0.9395
0.1578	2.0	3126	0.1547	0.9501
0.1132	3.0	4689	0.2315	0.9490
0.0801	4.0	6252	0.2392	0.9478
0.0455	5.0	7815	0.3256	0.9475
0.0377	6.0	9378	0.3895	0.9394
0.0299	7.0	10941	0.3465	0.9486
0.0199	8.0	12504	0.3895	0.9427
0.0232	9.0	14067	0.3813	0.945
0.0158	10.0	15630	0.4284	0.9476
0.0122	11.0	17193	0.4631	0.943
0.0094	12.0	18756	0.4639	0.9500
0.0074	13.0	20319	0.4256	0.9509
0.0032	14.0	21882	0.4599	0.9520
0.002	15.0	23445	0.5557	0.949
0.0025	16.0	25008	0.5381	0.9490
0.0018	17.0	26571	0.5017	0.9514
0.0008	18.0	28134	0.5676	0.9506
0.0	19.0	29697	0.5757	0.9519
0.0018	20.0	31260	0.5709	0.9526

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3