pytorch tensorboard xlm-roberta text-classification dataset:glue transformers generated_from_trainer license:agpl-3.0 model-index
---
license: agpl-3.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: XLMR-ENIS-finetuned-sst2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9277522935779816
---

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# XLMR-ENIS-finetuned-sst2

This model is a fine-tuned version of [vesteinn/XLMR-ENIS](https://huggingface.co/vesteinn/XLMR-ENIS) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3781
- Accuracy: 0.9278

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0675        | 1.0   | 4210 | 0.3781          | 0.9278   |


### Framework versions

- Transformers 4.11.0
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
