| --- |
| license: mit |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: microsoft/phi-1_5 |
| 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-1_5](https://huggingface.co/microsoft/phi-1_5) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4965 |
|
|
| ## 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: 50 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 3.9692 | 0.95 | 5 | 3.7663 | |
| | 3.8826 | 1.9 | 10 | 3.6222 | |
| | 3.7248 | 2.86 | 15 | 3.4342 | |
| | 2.8804 | 4.0 | 21 | 3.1608 | |
| | 3.1948 | 4.95 | 26 | 2.8958 | |
| | 2.9136 | 5.9 | 31 | 2.6167 | |
| | 2.5989 | 6.86 | 36 | 2.2949 | |
| | 1.869 | 8.0 | 42 | 1.8694 | |
| | 1.8586 | 8.95 | 47 | 1.5201 | |
| | 1.5399 | 9.9 | 52 | 1.2544 | |
| | 1.3188 | 10.86 | 57 | 1.1105 | |
| | 0.9827 | 12.0 | 63 | 0.9700 | |
| | 1.0818 | 12.95 | 68 | 0.8830 | |
| | 0.9514 | 13.9 | 73 | 0.8180 | |
| | 0.903 | 14.86 | 78 | 0.7661 | |
| | 0.6992 | 16.0 | 84 | 0.7211 | |
| | 0.7744 | 16.95 | 89 | 0.6985 | |
| | 0.7585 | 17.9 | 94 | 0.6771 | |
| | 0.7381 | 18.86 | 99 | 0.6627 | |
| | 0.5829 | 20.0 | 105 | 0.6441 | |
| | 0.6846 | 20.95 | 110 | 0.6344 | |
| | 0.6616 | 21.9 | 115 | 0.6242 | |
| | 0.622 | 22.86 | 120 | 0.6125 | |
| | 0.512 | 24.0 | 126 | 0.6008 | |
| | 0.5945 | 24.95 | 131 | 0.5926 | |
| | 0.5956 | 25.9 | 136 | 0.5843 | |
| | 0.5672 | 26.86 | 141 | 0.5782 | |
| | 0.4526 | 28.0 | 147 | 0.5681 | |
| | 0.5338 | 28.95 | 152 | 0.5603 | |
| | 0.5228 | 29.9 | 157 | 0.5548 | |
| | 0.5295 | 30.86 | 162 | 0.5474 | |
| | 0.4214 | 32.0 | 168 | 0.5435 | |
| | 0.4929 | 32.95 | 173 | 0.5363 | |
| | 0.4764 | 33.9 | 178 | 0.5330 | |
| | 0.4804 | 34.86 | 183 | 0.5274 | |
| | 0.3795 | 36.0 | 189 | 0.5230 | |
| | 0.4529 | 36.95 | 194 | 0.5176 | |
| | 0.4614 | 37.9 | 199 | 0.5139 | |
| | 0.4334 | 38.86 | 204 | 0.5110 | |
| | 0.3623 | 40.0 | 210 | 0.5072 | |
| | 0.4472 | 40.95 | 215 | 0.5059 | |
| | 0.4261 | 41.9 | 220 | 0.5024 | |
| | 0.4203 | 42.86 | 225 | 0.5017 | |
| | 0.3447 | 44.0 | 231 | 0.4982 | |
| | 0.4222 | 44.95 | 236 | 0.4977 | |
| | 0.4143 | 45.9 | 241 | 0.4970 | |
| | 0.4103 | 46.86 | 246 | 0.4966 | |
| | 0.3427 | 47.62 | 250 | 0.4965 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.10.0 |
| - Transformers 4.38.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.1.0 |
| - Tokenizers 0.15.2 |
