metadata
license: gemma
base_model: google/gemma-2-9b
tags:
- easylm
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- alpaca_farm
model-index:
- name: easylm-sft-gemma-2-9b
results: []
easylm-sft-gemma-2-9b
This model is a fine-tuned version of google/gemma-2-9b on the alpaca_farm dataset. It achieves the following results on the evaluation set:
- Loss: 0.7115
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6921 | 0.016 | 10 | 0.6721 |
0.6141 | 0.032 | 20 | 0.6662 |
0.6665 | 0.048 | 30 | 0.6603 |
0.6116 | 0.064 | 40 | 0.6611 |
0.6102 | 0.08 | 50 | 0.6580 |
0.6886 | 0.096 | 60 | 0.6593 |
0.6415 | 0.112 | 70 | 0.6596 |
0.6214 | 0.128 | 80 | 0.6595 |
0.6816 | 0.144 | 90 | 0.6584 |
0.6481 | 0.16 | 100 | 0.6597 |
0.6022 | 0.176 | 110 | 0.6590 |
0.6703 | 0.192 | 120 | 0.6607 |
0.6742 | 0.208 | 130 | 0.6615 |
0.6369 | 0.224 | 140 | 0.6615 |
0.7142 | 0.24 | 150 | 0.6602 |
0.6707 | 0.256 | 160 | 0.6611 |
0.6629 | 0.272 | 170 | 0.6609 |
0.6299 | 0.288 | 180 | 0.6610 |
0.6351 | 0.304 | 190 | 0.6607 |
0.5885 | 0.32 | 200 | 0.6610 |
0.6613 | 0.336 | 210 | 0.6619 |
0.6151 | 0.352 | 220 | 0.6602 |
0.6342 | 0.368 | 230 | 0.6609 |
0.6376 | 0.384 | 240 | 0.6601 |
0.679 | 0.4 | 250 | 0.6601 |
0.6911 | 0.416 | 260 | 0.6593 |
0.6717 | 0.432 | 270 | 0.6592 |
0.6758 | 0.448 | 280 | 0.6603 |
0.6243 | 0.464 | 290 | 0.6603 |
0.643 | 0.48 | 300 | 0.6586 |
0.603 | 0.496 | 310 | 0.6573 |
0.6336 | 0.512 | 320 | 0.6568 |
0.6198 | 0.528 | 330 | 0.6569 |
0.6989 | 0.544 | 340 | 0.6578 |
0.6353 | 0.56 | 350 | 0.6570 |
0.6746 | 0.576 | 360 | 0.6568 |
0.6883 | 0.592 | 370 | 0.6571 |
0.6772 | 0.608 | 380 | 0.6566 |
0.6563 | 0.624 | 390 | 0.6564 |
0.6077 | 0.64 | 400 | 0.6554 |
0.6291 | 0.656 | 410 | 0.6552 |
0.6073 | 0.672 | 420 | 0.6547 |
0.6598 | 0.688 | 430 | 0.6551 |
0.593 | 0.704 | 440 | 0.6547 |
0.6352 | 0.72 | 450 | 0.6547 |
0.6216 | 0.736 | 460 | 0.6540 |
0.6937 | 0.752 | 470 | 0.6535 |
0.669 | 0.768 | 480 | 0.6530 |
0.6052 | 0.784 | 490 | 0.6525 |
0.6218 | 0.8 | 500 | 0.6525 |
0.6341 | 0.816 | 510 | 0.6526 |
0.6681 | 0.832 | 520 | 0.6522 |
0.6203 | 0.848 | 530 | 0.6516 |
0.6682 | 0.864 | 540 | 0.6506 |
0.6212 | 0.88 | 550 | 0.6501 |
0.6887 | 0.896 | 560 | 0.6502 |
0.64 | 0.912 | 570 | 0.6504 |
0.6176 | 0.928 | 580 | 0.6500 |
0.6285 | 0.944 | 590 | 0.6500 |
0.6661 | 0.96 | 600 | 0.6489 |
0.6537 | 0.976 | 610 | 0.6488 |
0.657 | 0.992 | 620 | 0.6482 |
0.4004 | 1.008 | 630 | 0.6503 |
0.4014 | 1.024 | 640 | 0.7170 |
0.4179 | 1.04 | 650 | 0.6923 |
0.3998 | 1.056 | 660 | 0.6921 |
0.3705 | 1.072 | 670 | 0.7054 |
0.3513 | 1.088 | 680 | 0.7036 |
0.3815 | 1.104 | 690 | 0.7025 |
0.3684 | 1.12 | 700 | 0.7049 |
0.3914 | 1.1360 | 710 | 0.7069 |
0.4082 | 1.152 | 720 | 0.7018 |
0.3494 | 1.168 | 730 | 0.7042 |
0.3715 | 1.184 | 740 | 0.7071 |
0.3675 | 1.2 | 750 | 0.7085 |
0.3319 | 1.216 | 760 | 0.7112 |
0.3823 | 1.232 | 770 | 0.7141 |
0.3571 | 1.248 | 780 | 0.7113 |
0.3503 | 1.264 | 790 | 0.7127 |
0.3742 | 1.28 | 800 | 0.7159 |
0.4087 | 1.296 | 810 | 0.7139 |
0.3781 | 1.312 | 820 | 0.7073 |
0.3475 | 1.328 | 830 | 0.7129 |
0.3724 | 1.3440 | 840 | 0.7113 |
0.3612 | 1.3600 | 850 | 0.7130 |
0.3254 | 1.376 | 860 | 0.7139 |
0.3626 | 1.392 | 870 | 0.7145 |
0.351 | 1.408 | 880 | 0.7147 |
0.3357 | 1.424 | 890 | 0.7105 |
0.371 | 1.44 | 900 | 0.7079 |
0.3566 | 1.456 | 910 | 0.7070 |
0.3762 | 1.472 | 920 | 0.7118 |
0.3755 | 1.488 | 930 | 0.7126 |
0.3595 | 1.504 | 940 | 0.7107 |
0.3828 | 1.52 | 950 | 0.7118 |
0.3793 | 1.536 | 960 | 0.7173 |
0.3446 | 1.552 | 970 | 0.7150 |
0.3707 | 1.568 | 980 | 0.7135 |
0.3604 | 1.584 | 990 | 0.7141 |
0.3441 | 1.6 | 1000 | 0.7137 |
0.3705 | 1.616 | 1010 | 0.7154 |
0.3857 | 1.6320 | 1020 | 0.7189 |
0.3952 | 1.6480 | 1030 | 0.7148 |
0.3815 | 1.6640 | 1040 | 0.7116 |
0.3507 | 1.6800 | 1050 | 0.7108 |
0.3662 | 1.696 | 1060 | 0.7124 |
0.3581 | 1.712 | 1070 | 0.7136 |
0.3867 | 1.728 | 1080 | 0.7132 |
0.3707 | 1.744 | 1090 | 0.7127 |
0.4078 | 1.76 | 1100 | 0.7122 |
0.3713 | 1.776 | 1110 | 0.7111 |
0.3525 | 1.792 | 1120 | 0.7110 |
0.3873 | 1.808 | 1130 | 0.7115 |
0.4008 | 1.8240 | 1140 | 0.7119 |
0.3889 | 1.8400 | 1150 | 0.7119 |
0.3591 | 1.8560 | 1160 | 0.7116 |
0.3843 | 1.8720 | 1170 | 0.7116 |
0.3713 | 1.888 | 1180 | 0.7115 |
0.3659 | 1.904 | 1190 | 0.7115 |
0.3588 | 1.92 | 1200 | 0.7115 |
0.3556 | 1.936 | 1210 | 0.7115 |
0.3278 | 1.952 | 1220 | 0.7116 |
0.3642 | 1.968 | 1230 | 0.7115 |
0.3718 | 1.984 | 1240 | 0.7115 |
0.3611 | 2.0 | 1250 | 0.7115 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1