--- 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](https://huggingface.co/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