---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_roberta_imdb_padding30model
  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: 0.95048
---

<!-- 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_padding30model

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: 0.4323
- Accuracy: 0.9505

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2137        | 1.0   | 1563  | 0.2731          | 0.9326   |
| 0.1664        | 2.0   | 3126  | 0.1977          | 0.9475   |
| 0.1079        | 3.0   | 4689  | 0.2742          | 0.9441   |
| 0.0728        | 4.0   | 6252  | 0.2245          | 0.9474   |
| 0.0479        | 5.0   | 7815  | 0.2897          | 0.9496   |
| 0.0405        | 6.0   | 9378  | 0.3329          | 0.9473   |
| 0.0428        | 7.0   | 10941 | 0.3308          | 0.9452   |
| 0.0285        | 8.0   | 12504 | 0.3586          | 0.9468   |
| 0.0242        | 9.0   | 14067 | 0.3599          | 0.9459   |
| 0.0193        | 10.0  | 15630 | 0.3755          | 0.9444   |
| 0.0133        | 11.0  | 17193 | 0.3994          | 0.9445   |
| 0.0178        | 12.0  | 18756 | 0.3940          | 0.9486   |
| 0.0081        | 13.0  | 20319 | 0.4090          | 0.9479   |
| 0.0064        | 14.0  | 21882 | 0.4170          | 0.9500   |
| 0.004         | 15.0  | 23445 | 0.4484          | 0.9434   |
| 0.0031        | 16.0  | 25008 | 0.4368          | 0.9484   |
| 0.0043        | 17.0  | 26571 | 0.4170          | 0.9496   |
| 0.0053        | 18.0  | 28134 | 0.4129          | 0.9501   |
| 0.0026        | 19.0  | 29697 | 0.4325          | 0.9498   |
| 0.0029        | 20.0  | 31260 | 0.4323          | 0.9505   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3