---
license: mit
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: sa_english_new
  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: 0.9394
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sa_english_new

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3371
- Accuracy: 0.9394

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.244         | 1.0   | 1563 | 0.2231          | 0.9151   |
| 0.1826        | 2.0   | 3126 | 0.2054          | 0.9396   |
| 0.1196        | 3.0   | 4689 | 0.2671          | 0.9350   |
| 0.0769        | 4.0   | 6252 | 0.2950          | 0.9399   |
| 0.0455        | 5.0   | 7815 | 0.3371          | 0.9394   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3