| | --- |
| | license: mit |
| | library_name: peft |
| | tags: |
| | - generated_from_trainer |
| | base_model: microsoft/Phi-3-mini-128k-instruct |
| | model-index: |
| | - name: working |
| | 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. --> |
| |
|
| | # working |
| |
|
| | This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6374 |
| |
|
| | ## 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: 6 |
| | - eval_batch_size: 6 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 24 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 2 |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 2.6546 | 0.92 | 6 | 1.7189 | |
| | | 1.2076 | 2.0 | 13 | 0.8973 | |
| | | 0.7157 | 2.92 | 19 | 0.5511 | |
| | | 0.4138 | 4.0 | 26 | 0.4499 | |
| | | 0.4018 | 4.92 | 32 | 0.4044 | |
| | | 0.3034 | 6.0 | 39 | 0.3793 | |
| | | 0.3186 | 6.92 | 45 | 0.3645 | |
| | | 0.2451 | 8.0 | 52 | 0.3590 | |
| | | 0.2556 | 8.92 | 58 | 0.3660 | |
| | | 0.1937 | 10.0 | 65 | 0.3825 | |
| | | 0.1993 | 10.92 | 71 | 0.3782 | |
| | | 0.1511 | 12.0 | 78 | 0.4275 | |
| | | 0.1487 | 12.92 | 84 | 0.4234 | |
| | | 0.1098 | 14.0 | 91 | 0.4876 | |
| | | 0.1121 | 14.92 | 97 | 0.4675 | |
| | | 0.0846 | 16.0 | 104 | 0.5187 | |
| | | 0.0869 | 16.92 | 110 | 0.5365 | |
| | | 0.0677 | 18.0 | 117 | 0.5372 | |
| | | 0.0729 | 18.92 | 123 | 0.5639 | |
| | | 0.0587 | 20.0 | 130 | 0.5773 | |
| | | 0.0623 | 20.92 | 136 | 0.6006 | |
| | | 0.0524 | 22.0 | 143 | 0.6098 | |
| | | 0.0599 | 22.92 | 149 | 0.6101 | |
| | | 0.0495 | 24.0 | 156 | 0.6204 | |
| | | 0.0571 | 24.92 | 162 | 0.6297 | |
| | | 0.0475 | 26.0 | 169 | 0.6353 | |
| | | 0.0551 | 26.92 | 175 | 0.6374 | |
| | | 0.0455 | 27.69 | 180 | 0.6374 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.10.0 |
| | - Transformers 4.39.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
