deberta_v3_finetune_hellaswag

This model is a fine-tuned version of microsoft/deberta-v3-base on an the hellaswag dataset. It achieves the following results on the evaluation set:

• Loss: 0.3999
• Accuracy: 0.8765

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5083	0.9996	1247	0.3641	0.8622
0.193	1.9992	2494	0.3999	0.8765

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.19.1