metadata

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: []

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 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