fine_tune_output_llama_3.2_3B_Instruct

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8439

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
5.3098	0.0170	10	4.6081
3.4781	0.0340	20	3.3873
2.7865	0.0510	30	2.4973
1.3726	0.0679	40	1.5682
1.2072	0.0849	50	0.9569
1.258	0.1019	60	0.8688
1.3057	0.1189	70	0.8637
0.7572	0.1359	80	0.8554
1.212	0.1529	90	0.8531
0.5833	0.1699	100	0.8439

Framework versions

• PEFT 0.10.0
• Transformers 4.44.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.19.1