fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arcchallenge

This model is a fine-tuned version of MoritzLaurer/deberta-v3-large-zeroshot-v2.0 on ARC-Challenge dataset. It achieves the following results on the evaluation set:

• Loss: 1.6476
• Accuracy: 0.6087

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: 1.5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	70	0.9709	0.6421
No log	2.0	140	1.0093	0.6321
No log	3.0	210	1.2280	0.6455
No log	4.0	280	1.4439	0.6355
No log	5.0	350	1.6110	0.6120
No log	6.0	420	1.6476	0.6087

Framework versions

• PEFT 0.11.1
• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1