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xlmr-finetuned-ner – AI Model by Andrey1989 | AlphaNeural AI
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Andrey1989
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xlmr-finetuned-ner
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
wikiann
mit
model-index
autotrain_compatible
endpoints_compatible
us
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xlmr-finetuned-ner
This model is a fine-tuned version of
xlm-roberta-base
on the wikiann dataset. It achieves the following results on the evaluation set:
Loss: 0.1395
Precision: 0.9044
Recall: 0.9137
F1: 0.9090
Accuracy: 0.9649
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
Precision
Recall
F1
Accuracy
0.4215
1.0
938
0.1650
0.8822
0.8781
0.8802
0.9529
0.1559
2.0
1876
0.1412
0.9018
0.9071
0.9045
0.9631
0.1051
3.0
2814
0.1395
0.9044
0.9137
0.9090
0.9649
Framework versions
Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1
