---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_roberta_imdb_padding100model
  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: 0.94956
---

<!-- 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_padding100model

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: 0.4217
- Accuracy: 0.9496

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2097        | 1.0   | 1563  | 0.1893          | 0.9421   |
| 0.1725        | 2.0   | 3126  | 0.1588          | 0.9470   |
| 0.1091        | 3.0   | 4689  | 0.2349          | 0.9444   |
| 0.0796        | 4.0   | 6252  | 0.2474          | 0.9435   |
| 0.0543        | 5.0   | 7815  | 0.2866          | 0.9453   |
| 0.0387        | 6.0   | 9378  | 0.3219          | 0.9452   |
| 0.0252        | 7.0   | 10941 | 0.3410          | 0.9443   |
| 0.0278        | 8.0   | 12504 | 0.3811          | 0.9447   |
| 0.0234        | 9.0   | 14067 | 0.3518          | 0.9459   |
| 0.0177        | 10.0  | 15630 | 0.3733          | 0.9437   |
| 0.0247        | 11.0  | 17193 | 0.3569          | 0.9481   |
| 0.0118        | 12.0  | 18756 | 0.3711          | 0.9441   |
| 0.0166        | 13.0  | 20319 | 0.3597          | 0.9470   |
| 0.0109        | 14.0  | 21882 | 0.4184          | 0.9498   |
| 0.0046        | 15.0  | 23445 | 0.4363          | 0.9438   |
| 0.0046        | 16.0  | 25008 | 0.4597          | 0.9467   |
| 0.0057        | 17.0  | 26571 | 0.4282          | 0.9481   |
| 0.0045        | 18.0  | 28134 | 0.4345          | 0.9482   |
| 0.0056        | 19.0  | 29697 | 0.4097          | 0.9493   |
| 0.0022        | 20.0  | 31260 | 0.4217          | 0.9496   |


### Framework versions

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