---
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
---

<!-- 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_padding90model

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: 0.4435
- 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