results_german – AI Model by AvianaKahn | AlphaNeural AI

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AvianaKahn/
results_german

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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results_german

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3821
Accuracy: 0.6464
Precision: 0.6635
Recall: 0.6464
F1: 0.6480

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	181	1.0217	0.5276	0.4372	0.5276	0.4522
No log	2.0	362	0.9691	0.5359	0.6815	0.5359	0.4655
0.9831	3.0	543	0.9005	0.6077	0.6064	0.6077	0.6057
0.9831	4.0	724	0.8882	0.6243	0.6475	0.6243	0.6268
0.9831	5.0	905	0.9119	0.6243	0.6576	0.6243	0.6286
0.725	6.0	1086	0.9493	0.6492	0.6588	0.6492	0.6512
0.725	7.0	1267	1.0316	0.6409	0.6617	0.6409	0.6419
0.725	8.0	1448	1.1723	0.6492	0.6529	0.6492	0.6500
0.5024	9.0	1629	1.3081	0.6271	0.6335	0.6271	0.6288
0.5024	10.0	1810	1.3821	0.6464	0.6635	0.6464	0.6480

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1