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---
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 |