results_1011 – AI Model by Jsoo | AlphaNeural AI

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results_1011

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

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results_1011

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: 1.9956

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: 3
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 24
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.01
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.6788	0.3901	100	2.2881
2.4361	0.7801	200	2.2154
2.3903	1.1702	300	2.1747
2.3166	1.5602	400	2.1358
2.2868	1.9503	500	2.1058
2.2048	2.3403	600	2.0800
2.1999	2.7304	700	2.0613
2.1711	3.1204	800	2.0471
2.1038	3.5105	900	2.0329
2.1115	3.9005	1000	2.0185
2.0859	4.2906	1100	2.0129
2.0455	4.6806	1200	2.0084
2.0338	5.0707	1300	2.0022
1.9991	5.4608	1400	2.0011
1.9948	5.8508	1500	1.9966
1.948	6.2409	1600	1.9977
1.9773	6.6309	1700	1.9909
1.9228	7.0210	1800	1.9915
1.8997	7.4110	1900	1.9947
1.9212	7.8011	2000	1.9868
1.8786	8.1911	2100	2.0092
1.8762	8.5812	2200	2.0070
1.8724	8.9712	2300	2.0023
1.8604	9.3613	2400	1.9978
1.8436	9.7513	2500	1.9956

Framework versions

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