---
license: mit
base_model: xlm-roberta-base
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: 0.8699106256206554
---

<!-- 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: 0.5351
- F1: 0.8699

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.843         | 1.0   | 86   | 0.3921          | 0.7206 |
| 0.3751        | 2.0   | 172  | 0.3292          | 0.7381 |
| 0.2437        | 3.0   | 258  | 0.3049          | 0.8255 |
| 0.1963        | 4.0   | 344  | 0.2865          | 0.8255 |
| 0.1519        | 5.0   | 430  | 0.3165          | 0.8422 |
| 0.1332        | 6.0   | 516  | 0.3019          | 0.8433 |
| 0.0748        | 7.0   | 602  | 0.3290          | 0.8474 |
| 0.0703        | 8.0   | 688  | 0.3825          | 0.8517 |
| 0.0611        | 9.0   | 774  | 0.4575          | 0.8518 |
| 0.0484        | 10.0  | 860  | 0.4409          | 0.8481 |
| 0.0345        | 11.0  | 946  | 0.4221          | 0.8597 |
| 0.0242        | 12.0  | 1032 | 0.4673          | 0.8682 |
| 0.0178        | 13.0  | 1118 | 0.4826          | 0.8671 |
| 0.0129        | 14.0  | 1204 | 0.5174          | 0.8443 |
| 0.0139        | 15.0  | 1290 | 0.5028          | 0.8608 |
| 0.0063        | 16.0  | 1376 | 0.5224          | 0.8648 |
| 0.0027        | 17.0  | 1462 | 0.5260          | 0.8682 |
| 0.0036        | 18.0  | 1548 | 0.5301          | 0.8702 |
| 0.0028        | 19.0  | 1634 | 0.5372          | 0.8741 |
| 0.0038        | 20.0  | 1720 | 0.5351          | 0.8699 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3