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lataon/
finetune

meta-llama/Llama-3.2-1B-Instruct

llama3.2

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finetune

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: 0.3303

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: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
1.0733	0.2	5	0.8342
0.5412	0.4	10	0.5452
0.482	0.6	15	0.4806
0.372	0.8	20	0.4173
0.3336	1.0	25	0.3932
0.3449	1.2	30	0.3777
0.3247	1.4	35	0.3705
0.3711	1.6	40	0.3568
0.2638	1.8	45	0.3480
0.2707	2.0	50	0.3436
0.2652	2.2	55	0.3407
0.2703	2.4	60	0.3369
0.2841	2.6	65	0.3350
0.2334	2.8	70	0.3302
0.2854	3.0	75	0.3303

Framework versions

PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

lataon/finetune

finetune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lataon/
finetune