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xlmr-vi-nli – AI Model by lyle49 | AlphaNeural AI
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xlmr-vi-nli
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safetensors
xlm-roberta
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
us
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xlmr-vi-nli
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: 0.2354
Accuracy: 0.9796
F1 Macro: 0.9796
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: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
0.2665
0.9994
882
0.2531
0.9745
0.9745
0.2312
2.0
1765
0.2445
0.9756
0.9756
0.1965
2.9994
2647
0.2278
0.9807
0.9808
0.1829
3.9977
3528
0.2312
0.9807
0.9807
Framework versions
Transformers 4.43.3
Pytorch 2.6.0+cu124
Datasets 2.21.0
Tokenizers 0.19.1
