xlm-r-langdetect-model – AI Model by SongJuNN | AlphaNeural AI

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SongJuNN/
xlm-r-langdetect-model

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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xlm-r-langdetect-model

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

Loss: 0.2107
Accuracy: 0.9617

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: 128
eval_batch_size: 256
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1059	1.0	1275	0.1641	0.9526
0.0838	2.0	2550	0.1660	0.9548
0.068	3.0	3825	0.1741	0.9552
0.0561	4.0	5100	0.1828	0.9556
0.0474	5.0	6375	0.1918	0.9549
0.0428	6.0	7650	0.1994	0.9568
0.0346	7.0	8925	0.2109	0.9568
0.0351	8.0	10200	0.2138	0.9588
0.0318	9.0	11475	0.2218	0.9588
0.0282	10.0	12750	0.2219	0.9593

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1