results_llama_1b_fim
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: 1.2295
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3165 | 0.2862 | 1000 | 1.2803 |
| 1.284 | 0.5723 | 2000 | 1.2618 |
| 1.2053 | 0.8585 | 3000 | 1.2515 |
| 1.2116 | 1.1445 | 4000 | 1.2452 |
| 1.1882 | 1.4307 | 5000 | 1.2404 |
| 1.2239 | 1.7168 | 6000 | 1.2362 |
| 1.2575 | 2.0029 | 7000 | 1.2335 |
| 1.2141 | 2.2890 | 8000 | 1.2318 |
| 1.2308 | 2.5752 | 9000 | 1.2304 |
| 1.2718 | 2.8614 | 10000 | 1.2295 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 2.17.0
- Tokenizers 0.21.0
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Base model
meta-llama/Llama-3.2-1B