malduwais/XLM-Roberta-base-Finetuned-EN-AR-ADAPTER

xlm-roberta-base-finetuned-Adapter-en-ar-mlm-0.15-large-29OCT

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: 2.2667
• Model Preparation Time: 0.0044

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time
3.9064	0.2498	1000	3.2366	0.0044
3.0641	0.4995	2000	2.7403	0.0044
2.8162	0.7493	3000	2.5485	0.0044
2.7054	0.9990	4000	2.4384	0.0044
2.6108	1.2488	5000	2.3627	0.0044
2.5357	1.4985	6000	2.3141	0.0044
2.5089	1.7483	7000	2.2847	0.0044
2.4931	1.9980	8000	2.2667	0.0044

Framework versions

• Transformers 4.43.4
• Pytorch 2.1.1+cu121
• Datasets 3.0.2
• Tokenizers 0.19.1