---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-hi
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: xtreme
      type: xtreme
      config: PAN-X.hi
      split: validation
      args: PAN-X.hi
    metrics:
    - name: F1
      type: f1
      value: 0.875
---

<!-- 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. -->

# xlm-roberta-base-finetuned-panx-hi

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2334
- F1: 0.875

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6369        | 1.0   | 188  | 0.2775          | 0.8157 |
| 0.2751        | 2.0   | 376  | 0.2537          | 0.8402 |
| 0.1737        | 3.0   | 564  | 0.2359          | 0.8606 |
| 0.1188        | 4.0   | 752  | 0.2334          | 0.875  |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3