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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-panx-en
results: []
---
# xlm-roberta-base-finetuned-panx-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base).
It achieves the following results on the evaluation set:
- Loss: 0.3905
- F1 Score: 0.6861
## Model description
This model is a fine-tuned version of xlm-roberta-base on the English subset of the PAN-X dataset for Named Entity Recognition (NER). The model has been fine-tuned to perform token classification tasks and is evaluated on its performance in identifying named entities in English text.
## Intended uses & limitations
### Intended uses:
Named Entity Recognition (NER) tasks specifically for English.
Token classification tasks involving English text.
### Limitations:
The model's performance is optimized for English and may not generalize well to other languages without further fine-tuning.
The model's predictions are based on the data it was trained on and may not handle out-of-domain data as effectively.d
## Training and evaluation data
The model was fine-tuned on the English subset of the PAN-X dataset, which includes labeled examples of named entities in English text. The evaluation data is a separate portion of the same dataset, used to assess the model's performance
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0479 | 1.0 | 50 | 0.4854 | 0.5857 |
| 0.4604 | 2.0 | 100 | 0.3995 | 0.6605 |
| 0.3797 | 3.0 | 150 | 0.3905 | 0.6861 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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