This model is a fine-tuned version of barc0/Llama-3.1-ARC-Potpourri-Transduction-8B on the barc0/100_subset_test_aug_100 dataset. It achieves the following results on the evaluation set:

Loss: 0.0128

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: 0.0002
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.0168	0.9989	451	0.0255
0.0092	2.0	903	0.0133
0.0019	2.9967	1353	0.0128

Framework versions

PEFT 0.13.2
Transformers 4.45.0.dev0
Pytorch 2.4.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

barc0/potpourri-testtime-finetuning-100_test_aug100

potpourri-testtime-finetuning-100_test_aug100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

barc0/
potpourri-testtime-finetuning-100_test_aug100