---
library_name: transformers
base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-english
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-finetuned-conll03-english-finetuned-ner-biomedical-spanish
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xlm-roberta-large-finetuned-conll03-english-finetuned-ner-biomedical-spanish

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1526
- Precision: 0.8568
- Recall: 0.8258
- F1: 0.8410
- Accuracy: 0.9542

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 379  | 0.8877          | 0.5421    | 0.4232 | 0.4754 | 0.7697   |
| 0.8712        | 2.0   | 758  | 0.7159          | 0.5625    | 0.4761 | 0.5157 | 0.8265   |
| 0.1507        | 3.0   | 1137 | 0.4917          | 0.6528    | 0.5265 | 0.5829 | 0.8724   |
| 0.0984        | 4.0   | 1516 | 0.3969          | 0.7123    | 0.6516 | 0.6806 | 0.9005   |
| 0.0984        | 5.0   | 1895 | 0.3112          | 0.7463    | 0.6452 | 0.6920 | 0.9090   |
| 0.0732        | 6.0   | 2274 | 0.2653          | 0.8166    | 0.7239 | 0.7674 | 0.9299   |
| 0.0561        | 7.0   | 2653 | 0.2200          | 0.8006    | 0.7148 | 0.7553 | 0.9308   |
| 0.0465        | 8.0   | 3032 | 0.1590          | 0.8451    | 0.7884 | 0.8158 | 0.9485   |
| 0.0465        | 9.0   | 3411 | 0.1526          | 0.8568    | 0.8258 | 0.8410 | 0.9542   |
| 0.0396        | 10.0  | 3790 | 0.1494          | 0.8493    | 0.8142 | 0.8314 | 0.9526   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3