File size: 2,910 Bytes
930295e 72bbc42 1ef0ea5 930295e 1ef0ea5 930295e 1ef0ea5 930295e 1ef0ea5 930295e 72bbc42 930295e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: microsoft/phi-2
model-index:
- name: phi2_fine_tune_istanbul_rugs
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. -->
# phi2_fine_tune_istanbul_rugs
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8105
## 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: 0.0008
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6408 | 0.72 | 10 | 0.5720 |
| 0.4116 | 1.45 | 20 | 0.5234 |
| 0.3467 | 2.17 | 30 | 0.5068 |
| 0.328 | 2.9 | 40 | 0.4990 |
| 0.3013 | 3.62 | 50 | 0.5022 |
| 0.267 | 4.34 | 60 | 0.5051 |
| 0.2407 | 5.07 | 70 | 0.5151 |
| 0.2084 | 5.79 | 80 | 0.5329 |
| 0.1821 | 6.52 | 90 | 0.5566 |
| 0.1635 | 7.24 | 100 | 0.5996 |
| 0.1431 | 7.96 | 110 | 0.6137 |
| 0.1164 | 8.69 | 120 | 0.6461 |
| 0.1045 | 9.41 | 130 | 0.6714 |
| 0.0903 | 10.14 | 140 | 0.6719 |
| 0.0773 | 10.86 | 150 | 0.6802 |
| 0.0653 | 11.58 | 160 | 0.7234 |
| 0.0595 | 12.31 | 170 | 0.7497 |
| 0.0523 | 13.03 | 180 | 0.7281 |
| 0.0453 | 13.76 | 190 | 0.7439 |
| 0.0405 | 14.48 | 200 | 0.7655 |
| 0.0363 | 15.2 | 210 | 0.7674 |
| 0.0323 | 15.93 | 220 | 0.7835 |
| 0.0293 | 16.65 | 230 | 0.7924 |
| 0.0276 | 17.38 | 240 | 0.7981 |
| 0.0257 | 18.1 | 250 | 0.8023 |
| 0.0252 | 18.82 | 260 | 0.8019 |
| 0.0236 | 19.55 | 270 | 0.8040 |
| 0.023 | 20.27 | 280 | 0.8089 |
| 0.0232 | 21.0 | 290 | 0.8104 |
| 0.0231 | 21.72 | 300 | 0.8105 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2 |