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XLMR-ENIS-finetuned-ner – AI Model by Titantoe | AlphaNeural AI
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XLMR-ENIS-finetuned-ner
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
mim_gold_ner
agpl-3.0
model-index
autotrain_compatible
endpoints_compatible
us
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XLMR-ENIS-finetuned-ner
This model is a fine-tuned version of
vesteinn/XLMR-ENIS
on the mim_gold_ner dataset. It achieves the following results on the evaluation set:
Loss: 0.0941
Precision: 0.8714
Recall: 0.8450
F1: 0.8580
Accuracy: 0.9827
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
0.0572
1.0
2904
0.0998
0.8586
0.8171
0.8373
0.9802
0.0313
2.0
5808
0.0868
0.8666
0.8288
0.8473
0.9822
0.0199
3.0
8712
0.0941
0.8714
0.8450
0.8580
0.9827
Framework versions
Transformers 4.11.2
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3
