transformers pytorch xlm-roberta text-classification generated_from_trainer dataset:xnli license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- xnli
license: mit
metrics:
- accuracy
tags:
- text-classification
- generated_from_trainer
model-index:
- name: xnli_xlm_r_only_de
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: xnli
      type: xnli
      config: de
      split: train
      args: de
    metrics:
    - type: accuracy
      value: 0.7863453815261044
      name: Accuracy
---

<!-- 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. -->

# xnli_xlm_r_only_de

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7212
- Accuracy: 0.7863

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.6876        | 1.0   | 3068  | 0.7671   | 0.5670          |
| 0.5323        | 2.0   | 6136  | 0.7972   | 0.5189          |
| 0.4652        | 3.0   | 9204  | 0.7928   | 0.5346          |
| 0.4089        | 4.0   | 12272 | 0.7940   | 0.5392          |
| 0.3614        | 5.0   | 15340 | 0.8092   | 0.5477          |
| 0.3173        | 6.0   | 18408 | 0.7920   | 0.6186          |
| 0.2805        | 7.0   | 21476 | 0.7936   | 0.6323          |
| 0.2496        | 8.0   | 24544 | 0.7960   | 0.6574          |
| 0.2246        | 9.0   | 27612 | 0.6894   | 0.7880          |
| 0.2068        | 10.0  | 30680 | 0.7212   | 0.7863          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
