| --- |
| base_model: meta-llama/Llama-3.1-8B-Instruct |
| library_name: peft |
| license: other |
| tags: |
| - llama-factory |
| - lora |
| - generated_from_trainer |
| model-index: |
| - name: climate |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # climate |
|
|
| This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the climate_1_day dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4520 |
|
|
| ## 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: 12 |
| - eval_batch_size: 12 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - total_train_batch_size: 24 |
| - total_eval_batch_size: 24 |
| - 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: cosine |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.8708 | 0.0267 | 10 | 1.7567 | |
| | 1.7168 | 0.0533 | 20 | 1.6884 | |
| | 1.6815 | 0.08 | 30 | 1.6499 | |
| | 1.6333 | 0.1067 | 40 | 1.6236 | |
| | 1.6028 | 0.1333 | 50 | 1.6039 | |
| | 1.5665 | 0.16 | 60 | 1.5895 | |
| | 1.574 | 0.1867 | 70 | 1.5772 | |
| | 1.5862 | 0.2133 | 80 | 1.5648 | |
| | 1.5218 | 0.24 | 90 | 1.5564 | |
| | 1.5451 | 0.2667 | 100 | 1.5466 | |
| | 1.5011 | 0.2933 | 110 | 1.5382 | |
| | 1.5182 | 0.32 | 120 | 1.5328 | |
| | 1.5331 | 0.3467 | 130 | 1.5240 | |
| | 1.5096 | 0.3733 | 140 | 1.5180 | |
| | 1.5433 | 0.4 | 150 | 1.5125 | |
| | 1.4919 | 0.4267 | 160 | 1.5082 | |
| | 1.5119 | 0.4533 | 170 | 1.5037 | |
| | 1.4898 | 0.48 | 180 | 1.4962 | |
| | 1.4879 | 0.5067 | 190 | 1.4910 | |
| | 1.4813 | 0.5333 | 200 | 1.4869 | |
| | 1.4776 | 0.56 | 210 | 1.4821 | |
| | 1.4786 | 0.5867 | 220 | 1.4783 | |
| | 1.4825 | 0.6133 | 230 | 1.4740 | |
| | 1.4525 | 0.64 | 240 | 1.4710 | |
| | 1.4794 | 0.6667 | 250 | 1.4680 | |
| | 1.4785 | 0.6933 | 260 | 1.4655 | |
| | 1.4523 | 0.72 | 270 | 1.4628 | |
| | 1.4618 | 0.7467 | 280 | 1.4605 | |
| | 1.4751 | 0.7733 | 290 | 1.4581 | |
| | 1.4263 | 0.8 | 300 | 1.4561 | |
| | 1.4421 | 0.8267 | 310 | 1.4548 | |
| | 1.4824 | 0.8533 | 320 | 1.4539 | |
| | 1.4675 | 0.88 | 330 | 1.4531 | |
| | 1.4891 | 0.9067 | 340 | 1.4525 | |
| | 1.4617 | 0.9333 | 350 | 1.4520 | |
| | 1.4404 | 0.96 | 360 | 1.4521 | |
| | 1.44 | 0.9867 | 370 | 1.4520 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.46.0 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.20.1 |
