| --- |
| license: other |
| library_name: peft |
| tags: |
| - llama-factory |
| - lora |
| - generated_from_trainer |
| base_model: microsoft/phi-2 |
| model-index: |
| - name: delphi |
| 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. --> |
|
|
| # delphi |
|
|
| This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the alpaca_gpt4_en dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8625 |
|
|
| ## 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: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 16 |
| - total_eval_batch_size: 2 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - num_epochs: 1.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.0325 | 0.07 | 200 | 0.8922 | |
| | 0.9136 | 0.14 | 400 | 0.8801 | |
| | 0.9043 | 0.21 | 600 | 0.8753 | |
| | 0.8903 | 0.27 | 800 | 0.8711 | |
| | 0.9056 | 0.34 | 1000 | 0.8683 | |
| | 0.9001 | 0.41 | 1200 | 0.8673 | |
| | 0.8949 | 0.48 | 1400 | 0.8668 | |
| | 0.8917 | 0.55 | 1600 | 0.8656 | |
| | 0.8951 | 0.62 | 1800 | 0.8648 | |
| | 0.9014 | 0.68 | 2000 | 0.8637 | |
| | 0.8874 | 0.75 | 2200 | 0.8630 | |
| | 0.8968 | 0.82 | 2400 | 0.8628 | |
| | 0.8755 | 0.89 | 2600 | 0.8626 | |
| | 0.9029 | 0.96 | 2800 | 0.8625 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.7.1 |
| - Transformers 4.36.1 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.14.5 |
| - Tokenizers 0.15.0 |
