---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# N_roberta_imdb_padding50model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/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