metadata

base_model: meta-llama/Llama-3.2-1B-Instruct
library_name: peft
license: llama3.2
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: llama3.2-1B-persianQAV2.0
    results: []

llama3.2-1B-persianQAV2.0

This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.4505
Model Preparation Time: 0.003

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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use adamw_torch 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: 0.15
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time
3.7277	0.1973	100	3.5422	0.003
3.1974	0.3947	200	2.8022	0.003
2.5995	0.5920	300	2.5565	0.003
2.5075	0.7893	400	2.5167	0.003
2.4734	0.9867	500	2.4958	0.003
2.4547	1.1845	600	2.4823	0.003
2.4308	1.3818	700	2.4721	0.003
2.4191	1.5792	800	2.4649	0.003
2.4162	1.7765	900	2.4593	0.003
2.4033	1.9739	1000	2.4559	0.003
2.4093	2.1717	1100	2.4534	0.003
2.3859	2.3690	1200	2.4518	0.003
2.3967	2.5664	1300	2.4510	0.003
2.3894	2.7637	1400	2.4506	0.003
2.3963	2.9610	1500	2.4505	0.003

Framework versions

PEFT 0.13.2
Transformers 4.46.1
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.20.1