llama3.2-3b-hard – AI Model by Jsoo | AlphaNeural AI

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Jsoo/
llama3.2-3b-hard

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meta-llama/Llama-3.2-3B-Instruct

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llama3.2-3b-hard

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0052

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: 0.0002
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.6035	0.5202	100	2.2469
2.412	1.0403	200	2.1836
2.3523	1.5605	300	2.1436
2.3063	2.0806	400	2.1116
2.24	2.6008	500	2.0822
2.2205	3.1209	600	2.0610
2.169	3.6411	700	2.0429
2.1232	4.1612	800	2.0338
2.1088	4.6814	900	2.0237
2.0885	5.2016	1000	2.0192
2.0604	5.7217	1100	2.0126
2.0353	6.2419	1200	2.0069
1.9994	6.7620	1300	2.0035
1.9972	7.2822	1400	2.0057
1.9674	7.8023	1500	1.9955
1.9455	8.3225	1600	2.0008
1.9392	8.8427	1700	2.0010
1.9339	9.3628	1800	2.0055
1.9034	9.8830	1900	1.9982
1.8877	10.4031	2000	2.0052

Framework versions

PEFT 0.12.0
Transformers 4.45.0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.1