metadata
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b-it
model-index:
- name: ft-google-gemma-2b-it-qlora-v2
results: []
ft-google-gemma-2b-it-qlora-v2
This model is a fine-tuned version of google/gemma-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.8028
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: 3e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2955 | 10.0 | 10 | 2.7587 |
| 0.232 | 20.0 | 20 | 2.5366 |
| 0.177 | 30.0 | 30 | 2.4293 |
| 0.1317 | 40.0 | 40 | 2.4247 |
| 0.0893 | 50.0 | 50 | 2.5725 |
| 0.0472 | 60.0 | 60 | 2.8254 |
| 0.0147 | 70.0 | 70 | 3.2230 |
| 0.0035 | 80.0 | 80 | 3.7653 |
| 0.0015 | 90.0 | 90 | 4.0707 |
| 0.0008 | 100.0 | 100 | 4.2730 |
| 0.0006 | 110.0 | 110 | 4.3961 |
| 0.0006 | 120.0 | 120 | 4.4900 |
| 0.0005 | 130.0 | 130 | 4.5394 |
| 0.0005 | 140.0 | 140 | 4.5999 |
| 0.0005 | 150.0 | 150 | 4.6447 |
| 0.0004 | 160.0 | 160 | 4.6848 |
| 0.0004 | 170.0 | 170 | 4.7255 |
| 0.0004 | 180.0 | 180 | 4.7569 |
| 0.0004 | 190.0 | 190 | 4.7802 |
| 0.0004 | 200.0 | 200 | 4.8020 |
| 0.0004 | 210.0 | 210 | 4.8522 |
| 0.0004 | 220.0 | 220 | 4.8690 |
| 0.0004 | 230.0 | 230 | 4.8940 |
| 0.0004 | 240.0 | 240 | 4.9423 |
| 0.0004 | 250.0 | 250 | 4.9723 |
| 0.0004 | 260.0 | 260 | 4.9644 |
| 0.0004 | 270.0 | 270 | 4.9923 |
| 0.0004 | 280.0 | 280 | 5.0230 |
| 0.0004 | 290.0 | 290 | 5.0319 |
| 0.0004 | 300.0 | 300 | 5.0627 |
| 0.0004 | 310.0 | 310 | 5.1078 |
| 0.0004 | 320.0 | 320 | 5.1167 |
| 0.0004 | 330.0 | 330 | 5.1260 |
| 0.0004 | 340.0 | 340 | 5.1586 |
| 0.0004 | 350.0 | 350 | 5.1803 |
| 0.0004 | 360.0 | 360 | 5.1652 |
| 0.0004 | 370.0 | 370 | 5.1692 |
| 0.0004 | 380.0 | 380 | 5.1980 |
| 0.0004 | 390.0 | 390 | 5.2254 |
| 0.0004 | 400.0 | 400 | 5.2434 |
| 0.0004 | 410.0 | 410 | 5.2792 |
| 0.0004 | 420.0 | 420 | 5.2699 |
| 0.0004 | 430.0 | 430 | 5.2906 |
| 0.0004 | 440.0 | 440 | 5.3069 |
| 0.0004 | 450.0 | 450 | 5.3063 |
| 0.0004 | 460.0 | 460 | 5.3275 |
| 0.0004 | 470.0 | 470 | 5.3406 |
| 0.0004 | 480.0 | 480 | 5.3319 |
| 0.0004 | 490.0 | 490 | 5.3354 |
| 0.0004 | 500.0 | 500 | 5.3601 |
| 0.0004 | 510.0 | 510 | 5.4094 |
| 0.0004 | 520.0 | 520 | 5.4175 |
| 0.0004 | 530.0 | 530 | 5.4083 |
| 0.0004 | 540.0 | 540 | 5.3947 |
| 0.0004 | 550.0 | 550 | 5.4211 |
| 0.0004 | 560.0 | 560 | 5.4287 |
| 0.0004 | 570.0 | 570 | 5.4580 |
| 0.0004 | 580.0 | 580 | 5.4610 |
| 0.0004 | 590.0 | 590 | 5.4775 |
| 0.0004 | 600.0 | 600 | 5.5165 |
| 0.0004 | 610.0 | 610 | 5.5356 |
| 0.0004 | 620.0 | 620 | 5.5142 |
| 0.0004 | 630.0 | 630 | 5.4963 |
| 0.0004 | 640.0 | 640 | 5.5114 |
| 0.0004 | 650.0 | 650 | 5.5223 |
| 0.0004 | 660.0 | 660 | 5.5468 |
| 0.0004 | 670.0 | 670 | 5.5543 |
| 0.0004 | 680.0 | 680 | 5.5731 |
| 0.0004 | 690.0 | 690 | 5.6010 |
| 0.0004 | 700.0 | 700 | 5.6050 |
| 0.0004 | 710.0 | 710 | 5.6203 |
| 0.0004 | 720.0 | 720 | 5.6415 |
| 0.0004 | 730.0 | 730 | 5.6312 |
| 0.0004 | 740.0 | 740 | 5.6209 |
| 0.0004 | 750.0 | 750 | 5.6283 |
| 0.0004 | 760.0 | 760 | 5.6605 |
| 0.0004 | 770.0 | 770 | 5.6683 |
| 0.0004 | 780.0 | 780 | 5.6686 |
| 0.0004 | 790.0 | 790 | 5.6810 |
| 0.0004 | 800.0 | 800 | 5.6837 |
| 0.0004 | 810.0 | 810 | 5.7018 |
| 0.0004 | 820.0 | 820 | 5.7189 |
| 0.0004 | 830.0 | 830 | 5.7218 |
| 0.0004 | 840.0 | 840 | 5.7053 |
| 0.0004 | 850.0 | 850 | 5.7328 |
| 0.0004 | 860.0 | 860 | 5.7495 |
| 0.0004 | 870.0 | 870 | 5.7220 |
| 0.0004 | 880.0 | 880 | 5.7142 |
| 0.0004 | 890.0 | 890 | 5.7272 |
| 0.0004 | 900.0 | 900 | 5.7643 |
| 0.0004 | 910.0 | 910 | 5.7750 |
| 0.0004 | 920.0 | 920 | 5.7762 |
| 0.0004 | 930.0 | 930 | 5.7899 |
| 0.0004 | 940.0 | 940 | 5.7878 |
| 0.0004 | 950.0 | 950 | 5.7727 |
| 0.0004 | 960.0 | 960 | 5.7630 |
| 0.0004 | 970.0 | 970 | 5.7806 |
| 0.0004 | 980.0 | 980 | 5.7953 |
| 0.0004 | 990.0 | 990 | 5.7662 |
| 0.0004 | 1000.0 | 1000 | 5.8028 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2