KAM-Llama3.2-3B
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the None dataset.
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: 1
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 1200
- mixed_precision_training: Native AMP
Training results
Step Training Loss
- 50 2.436700
- 100 2.103400
- 150 2.048900
- 200 2.041700
- 250 2.002900
- 300 1.991700
- 350 1.977400
- 400 1.974500
- 450 1.945000
- 500 1.951100
- 550 1.950700
- 600 1.943000
- 650 1.927900
- 700 1.920900
- 750 1.903400
- 800 1.896000
- 850 1.910800
- 900 1.904600
- 950 1.918100
- 1000 1.911500
- 1050 1.909100
- 1100 1.928900
- 1150 1.896100
- 1200 1.876700
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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Model tree for MaRyAm1295/Llama-3.2-3B-KAM
Base model
meta-llama/Llama-3.2-3B-Instruct