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tc-xlmr-viwikifc-finetuned-vihallu-fold-3 – AI Model by sercetexam9 | AlphaNeural AI
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sercetexam9
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tc-xlmr-viwikifc-finetuned-vihallu-fold-3
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transformers
safetensors
claim_verification
generated_from_trainer
SemViQA/tc-xlmr-viwikifc
finetune
mit
endpoints_compatible
us
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tc-xlmr-viwikifc-finetuned-vihallu-fold-3
This model is a fine-tuned version of
SemViQA/tc-xlmr-viwikifc
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5775
Accuracy: 0.8114
F1 Macro: 0.8120
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: 4
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
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: 0.1
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
0.6577
1.0
350
0.5663
0.7879
0.7876
0.4734
2.0
700
0.5775
0.8114
0.8120
Framework versions
Transformers 4.44.2
Pytorch 2.8.0+cu128
Datasets 2.20.0
Tokenizers 0.19.1