This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the HuggingFaceH4/deita-10k-v0-sft dataset. It achieves the following results on the evaluation set:

Loss: 1.2120

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 16
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
1.9906	1.0	15	1.1540
1.7061	2.0	30	1.1796
1.6448	3.0	45	1.2120

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2

RichardErkhov/Minbyul_-_llama2-7b-wo-kqa_golden-iter-sft-step1-4bits

Original model description:

llama2-7b-wo-kqa_golden-iter-sft-step1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
Minbyul_-_llama2-7b-wo-kqa_golden-iter-sft-step1-4bits