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multilingual_xlmr_v2 – AI Model by Yashaswini21 | AlphaNeural AI
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Yashaswini21
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multilingual_xlmr_v2
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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multilingual_xlmr_v2
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3044
Accuracy: 0.8662
Precision: 0.8835
Recall: 0.8437
F1: 0.8631
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: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.3315
1.0
3515
0.3428
0.8427
0.8920
0.7800
0.8322
0.3064
2.0
7030
0.3127
0.8593
0.9013
0.8070
0.8516
0.249
3.0
10545
0.3044
0.8662
0.8835
0.8437
0.8631
Framework versions
Transformers 4.55.2
Pytorch 2.8.0+cu129
Datasets 4.0.0
Tokenizers 0.21.4
