fine-tuned-visionllama
This model is a fine-tuned version of meta-llama/Llama-3.2-11B-Vision-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0321
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.179 | 0.2849 | 25 | 0.1736 |
| 0.1156 | 0.5698 | 50 | 0.1071 |
| 0.0531 | 0.8547 | 75 | 0.0782 |
| 0.0484 | 1.1396 | 100 | 0.0586 |
| 0.0224 | 1.4245 | 125 | 0.0365 |
| 0.0186 | 1.7094 | 150 | 0.0318 |
| 0.0178 | 1.9943 | 175 | 0.0351 |
| 0.019 | 2.2792 | 200 | 0.0356 |
| 0.0219 | 2.5641 | 225 | 0.0323 |
| 0.0123 | 2.8490 | 250 | 0.0321 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3
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Model tree for JohnFante/fine-tuned-visionllama
Base model
meta-llama/Llama-3.2-11B-Vision-Instruct