xlm-roberta-base-de-aug-ner – AI Model by Amir13 | AlphaNeural AI

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Amir13/
xlm-roberta-base-de-aug-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-de-aug-ner

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

Loss: 0.3820
Precision: 0.5214
Recall: 0.5660
F1: 0.5428
Accuracy: 0.8966

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	463	0.6140	0.2884	0.2925	0.2904	0.8438
0.8329	2.0	926	0.4504	0.4092	0.4423	0.4251	0.8720
0.4385	3.0	1389	0.4046	0.4634	0.5042	0.4829	0.8875
0.3364	4.0	1852	0.3843	0.5	0.5446	0.5213	0.8954
0.2919	5.0	2315	0.3820	0.5214	0.5660	0.5428	0.8966

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2