metadata
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- base_model:adapter:meta-llama/Llama-3.2-1B
- lora
- transformers
metrics:
- accuracy
model-index:
- name: edos_taskA_llama_allyears_lora2
results: []
edos_taskA_llama_allyears_lora2
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2633
- Accuracy: 0.9273
- F1 Macro: 0.9002
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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 1.2
- label_smoothing_factor: 0.05
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.9769 | 0.1068 | 100 | 0.4569 | 0.8135 | 0.7665 |
| 0.8868 | 0.2137 | 200 | 0.3733 | 0.8525 | 0.7959 |
| 0.8317 | 0.3205 | 300 | 0.3601 | 0.873 | 0.8254 |
| 0.7603 | 0.4274 | 400 | 0.3358 | 0.8845 | 0.8321 |
| 0.8641 | 0.5342 | 500 | 0.3237 | 0.8925 | 0.8481 |
| 0.6726 | 0.6410 | 600 | 0.2946 | 0.908 | 0.8730 |
| 0.6893 | 0.7479 | 700 | 0.2917 | 0.908 | 0.8621 |
| 0.6251 | 0.8547 | 800 | 0.2781 | 0.916 | 0.8855 |
| 0.636 | 0.9615 | 900 | 0.2657 | 0.9275 | 0.8979 |
| 0.499 | 1.0684 | 1000 | 0.2631 | 0.927 | 0.8991 |
| 0.4897 | 1.1752 | 1100 | 0.2596 | 0.928 | 0.9000 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.0