Llama-3.2-1B_v2
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2671
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.452 | 0.1 | 100 | 0.3832 |
0.3539 | 0.2 | 200 | 0.3223 |
0.2994 | 0.3 | 300 | 0.3045 |
0.2855 | 0.4 | 400 | 0.2919 |
0.2334 | 0.5 | 500 | 0.2832 |
0.2435 | 0.6 | 600 | 0.2761 |
0.3055 | 0.7 | 700 | 0.2716 |
0.2668 | 0.8 | 800 | 0.2687 |
0.2443 | 0.9 | 900 | 0.2674 |
0.2245 | 1.0 | 1000 | 0.2671 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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meta-llama/Llama-3.2-1B