This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the hansh/hansken_hql dataset. It achieves the following results on the evaluation set:

Loss: 0.2362

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: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
0.4508	0.9976	102	0.4433
0.302	1.9951	204	0.3140
0.2692	2.9927	306	0.2616
0.177	4.0	409	0.2431
0.1616	4.9976	511	0.2362
0.1358	5.9951	613	0.2394
0.1199	6.9927	715	0.2474
0.1051	8.0	818	0.2625
0.0945	8.9976	920	0.2797
0.0843	9.9951	1022	0.2892

Framework versions

PEFT 0.12.0
Transformers 4.44.0
Pytorch 2.1.2+cu121
Datasets 2.20.0
Tokenizers 0.19.1

hansh/hansken_human_hql

hansken_human_hql

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hansh/
hansken_human_hql