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---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
base_model: xlm-roberta-base
model-index:
- name: xlm-roberta-base-finetuned-panx-en
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: xtreme
type: xtreme
config: PAN-X.en
split: train
args: PAN-X.en
metrics:
- type: f1
value: 0.7023411371237458
name: F1
---
<!-- 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-en
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: 0.4292
- F1: 0.7023
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.99 | 73 | 0.5589 | 0.5660 |
| No log | 1.99 | 146 | 0.4565 | 0.6745 |
| No log | 2.99 | 219 | 0.4292 | 0.7023 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
|