metadata
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
results
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: 2.1652
- Accuracy: 0.0431
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6185 | 0.9970 | 82 | 2.6059 | 0.0323 |
| 2.4398 | 1.9939 | 164 | 2.6266 | 0.0582 |
| 2.4161 | 2.9909 | 246 | 2.3381 | 0.0905 |
| 2.3511 | 4.0 | 329 | 2.2989 | 0.1013 |
| 2.2733 | 4.9970 | 411 | 2.2880 | 0.0323 |
| 2.3463 | 5.9939 | 493 | 2.1652 | 0.0431 |
| 2.253 | 6.9909 | 575 | 2.1971 | 0.0431 |
| 2.2243 | 7.9757 | 656 | 2.1854 | 0.1272 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3