metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: fine-tuning-Phi2-with-webglm-qa-with-lora_6
results: []
fine-tuning-Phi2-with-webglm-qa-with-lora_6
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1212
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 7.3419 | 0.31 | 20 | 6.2616 |
| 4.0421 | 0.63 | 40 | 0.8963 |
| 0.6465 | 0.94 | 60 | 0.5726 |
| 0.4575 | 1.26 | 80 | 0.3999 |
| 0.309 | 1.57 | 100 | 0.3044 |
| 0.2531 | 1.89 | 120 | 0.2605 |
| 0.2235 | 2.2 | 140 | 0.2273 |
| 0.1922 | 2.52 | 160 | 0.2091 |
| 0.1793 | 2.83 | 180 | 0.1858 |
| 0.1488 | 3.14 | 200 | 0.1734 |
| 0.16 | 3.46 | 220 | 0.1646 |
| 0.1497 | 3.77 | 240 | 0.1557 |
| 0.1336 | 4.09 | 260 | 0.1489 |
| 0.1278 | 4.4 | 280 | 0.1415 |
| 0.1291 | 4.72 | 300 | 0.1392 |
| 0.1244 | 5.03 | 320 | 0.1342 |
| 0.1184 | 5.35 | 340 | 0.1319 |
| 0.118 | 5.66 | 360 | 0.1289 |
| 0.1153 | 5.97 | 380 | 0.1279 |
| 0.1052 | 6.29 | 400 | 0.1250 |
| 0.1058 | 6.6 | 420 | 0.1243 |
| 0.1142 | 6.92 | 440 | 0.1226 |
| 0.1026 | 7.23 | 460 | 0.1222 |
| 0.1051 | 7.55 | 480 | 0.1214 |
| 0.0977 | 7.86 | 500 | 0.1212 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0