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

Loss: 0.2505

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: 2
gradient_accumulation_steps: 2
total_train_batch_size: 4
total_eval_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.2781	0.7407	500	0.2681
0.1417	1.4815	1000	0.2399
0.0362	2.2222	1500	0.2555
0.0244	2.9630	2000	0.2507

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

RichardErkhov/shipWr3ck_-_toolalpaca-llama3.1-8b-Instruct-8bits

Original model description:

toolalpaca

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
shipWr3ck_-_toolalpaca-llama3.1-8b-Instruct-8bits