This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the PrincetonPLI/Instruct-SkillMix-SDD dataset. It achieves the following results on the evaluation set:

Loss: 1.7067

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-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 32
total_train_batch_size: 1024
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 1738
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.5333	1	1.8346
No log	1.6	3	1.7067

Framework versions

Transformers 4.44.2
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1

RichardErkhov/gsmyrnis_-_llama3_8b_baseline_instructskillmix-4bits

Original model description:

llama3_8b_baseline_instructskillmix

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
gsmyrnis_-_llama3_8b_baseline_instructskillmix-4bits