transformers pytorch roberta text-classification generated_from_trainer dataset:imdb base_model:FacebookAI/roberta-base base_model:finetune:FacebookAI/roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: roberta-base
datasets:
- imdb
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: N_roberta_imdb_padding0model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.95276
      name: Accuracy
---

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# N_roberta_imdb_padding0model

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: 0.5120
- Accuracy: 0.9528

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2059        | 1.0   | 1563  | 0.1926          | 0.9406   |
| 0.1663        | 2.0   | 3126  | 0.1661          | 0.9497   |
| 0.1024        | 3.0   | 4689  | 0.2261          | 0.9503   |
| 0.0691        | 4.0   | 6252  | 0.2616          | 0.9494   |
| 0.043         | 5.0   | 7815  | 0.3541          | 0.9466   |
| 0.0431        | 6.0   | 9378  | 0.3030          | 0.9522   |
| 0.0247        | 7.0   | 10941 | 0.3501          | 0.9482   |
| 0.0299        | 8.0   | 12504 | 0.3723          | 0.9478   |
| 0.02          | 9.0   | 14067 | 0.3530          | 0.9496   |
| 0.0204        | 10.0  | 15630 | 0.3836          | 0.9458   |
| 0.0144        | 11.0  | 17193 | 0.3471          | 0.9505   |
| 0.0095        | 12.0  | 18756 | 0.3696          | 0.9504   |
| 0.0087        | 13.0  | 20319 | 0.3877          | 0.9487   |
| 0.0078        | 14.0  | 21882 | 0.4487          | 0.9504   |
| 0.0056        | 15.0  | 23445 | 0.4657          | 0.9512   |
| 0.0032        | 16.0  | 25008 | 0.5004          | 0.9502   |
| 0.0041        | 17.0  | 26571 | 0.4863          | 0.9525   |
| 0.0036        | 18.0  | 28134 | 0.4833          | 0.9516   |
| 0.0           | 19.0  | 29697 | 0.5014          | 0.9523   |
| 0.0001        | 20.0  | 31260 | 0.5120          | 0.9528   |


### Framework versions

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