llama3.2-3b-medium
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: 1.6810
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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.0835 | 0.5198 | 100 | 1.9059 |
1.8694 | 1.0396 | 200 | 1.8444 |
1.7751 | 1.5595 | 300 | 1.8023 |
1.7621 | 2.0793 | 400 | 1.7662 |
1.6951 | 2.5991 | 500 | 1.7426 |
1.6917 | 3.1189 | 600 | 1.7270 |
1.6354 | 3.6387 | 700 | 1.7141 |
1.6231 | 4.1585 | 800 | 1.7076 |
1.5944 | 4.6784 | 900 | 1.6972 |
1.5959 | 5.1982 | 1000 | 1.6925 |
1.5429 | 5.7180 | 1100 | 1.6878 |
1.5584 | 6.2378 | 1200 | 1.6880 |
1.5347 | 6.7576 | 1300 | 1.6839 |
1.5536 | 7.2775 | 1400 | 1.6818 |
1.5061 | 7.7973 | 1500 | 1.6823 |
1.5282 | 8.3171 | 1600 | 1.6814 |
1.5187 | 8.8369 | 1700 | 1.6809 |
1.5232 | 9.3567 | 1800 | 1.6809 |
1.5131 | 9.8765 | 1900 | 1.6810 |
Framework versions
- PEFT 0.12.0
- Transformers 4.45.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1
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Model tree for Jsoo/llama3.2-3b-medium
Base model
meta-llama/Llama-3.2-3B-Instruct