metadata

license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: N_roberta_imdb_padding90model
    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: 0.951

N_roberta_imdb_padding90model

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

Loss: 0.4435
Accuracy: 0.951

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
0.21	1.0	1563	0.2359	0.9291
0.1649	2.0	3126	0.1754	0.9488
0.1154	3.0	4689	0.2331	0.944
0.0712	4.0	6252	0.2467	0.9473
0.0609	5.0	7815	0.3661	0.9428
0.0473	6.0	9378	0.3834	0.9435
0.0218	7.0	10941	0.4244	0.9434
0.0205	8.0	12504	0.4267	0.9446
0.0154	9.0	14067	0.3937	0.9460
0.0172	10.0	15630	0.4532	0.9476
0.0157	11.0	17193	0.4495	0.9462
0.0125	12.0	18756	0.4728	0.9452
0.0109	13.0	20319	0.4407	0.9494
0.0083	14.0	21882	0.4388	0.9474
0.0032	15.0	23445	0.4751	0.9467
0.0039	16.0	25008	0.4764	0.9481
0.0001	17.0	26571	0.4742	0.9501
0.0027	18.0	28134	0.4530	0.9509
0.0024	19.0	29697	0.4451	0.9508
0.0033	20.0	31260	0.4435	0.951

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3