metadata

base_model: MoritzLaurer/deberta-v3-base-zeroshot-v2.0
library_name: peft
license: mit
metrics:
  - accuracy
tags:
  - generated_from_trainer
model-index:
  - name: fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-arcchallenge
    results: []
datasets:
  - allenai/ai2_arc

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

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

Loss: 1.4473
Accuracy: 0.4983

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	1.2314	0.4515
No log	2.0	140	1.2478	0.4916
No log	3.0	210	1.2839	0.5184
No log	4.0	280	1.3545	0.4983
No log	5.0	350	1.4177	0.4916
No log	6.0	420	1.4473	0.4983

Framework versions

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