| --- |
| base_model: meta-llama/Meta-Llama-3-8B |
| datasets: |
| - HuggingFaceH4/ultrachat_200k |
| library_name: peft |
| license: llama3 |
| tags: |
| - alignment-handbook |
| - trl |
| - sft |
| - generated_from_trainer |
| model-index: |
| - name: llama3-sudo-sanity |
| 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. --> |
|
|
| # llama3-sudo-sanity |
|
|
| This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the HuggingFaceH4/ultrachat_200k dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1030 |
| |
| ## 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: 8 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - total_eval_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.8735 | 0.9899 | 49 | 1.8325 | |
| | 1.8231 | 2.0 | 99 | 1.7239 | |
| | 1.7516 | 2.9899 | 148 | 1.6330 | |
| | 1.6586 | 4.0 | 198 | 1.5280 | |
| | 1.5571 | 4.9899 | 247 | 1.4166 | |
| | 1.4677 | 6.0 | 297 | 1.3068 | |
| | 1.3422 | 6.9899 | 346 | 1.2082 | |
| | 1.2609 | 8.0 | 396 | 1.1378 | |
| | 1.1647 | 8.9899 | 445 | 1.1074 | |
| | 1.1571 | 9.8990 | 490 | 1.1030 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.44.0 |
| - Pytorch 2.1.2 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
