This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the identity and the labor20240807 datasets. It achieves the following results on the evaluation set:

Loss: 1.1235

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
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: 12.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.9225	3.6331	1000	1.1293
0.7145	7.2661	2000	1.1055
0.6401	10.8992	3000	1.1234

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1

RichardErkhov/clinno_-_labor-llama3-8b-Instruct-20241002-4bits

Original model description:

sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
clinno_-_labor-llama3-8b-Instruct-20241002-4bits