tc-xlmr-viwikifc-finetuned-vihallu-fold-4

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: 0.6241
• Accuracy: 0.7936
• F1 Macro: 0.7939

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
0.6376	1.0	350	0.6572	0.7693	0.7670
0.3878	2.0	700	0.6241	0.7936	0.7939

Framework versions

• Transformers 4.44.2
• Pytorch 2.8.0+cu128
• Datasets 2.20.0
• Tokenizers 0.19.1