This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the os-iter-plan-124 dataset. It achieves the following results on the evaluation set:

Loss: 0.1413

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 16
total_eval_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.1659	0.3317	100	0.1794
0.1577	0.6633	200	0.1611
0.1476	0.9950	300	0.1497
0.0819	1.3250	400	0.1501
0.0684	1.6567	500	0.1425
0.0665	1.9884	600	0.1414

Framework versions

Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Rain-air/Llama3-8B-osgenesis-plan-iter-sft_0125

sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Rain-air/
Llama3-8B-osgenesis-plan-iter-sft_0125