Mu7annad
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ner-xlm-roberta-english

Token Classification

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ner-xlm-roberta-english

This model is a fine-tuned version of xlm-roberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0445
F1 Score: 0.9452

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
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
0.1626	1.0	878	0.0554	0.9238
0.0404	2.0	1756	0.0465	0.9417
0.0237	3.0	2634	0.0445	0.9452

Framework versions

Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

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Safetensors

Model size

0.3B params

Tensor type

F32

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Dataset used to train Mu7annad/ner-xlm-roberta-english