metadata
base_model: google/gemma-2-9b
library_name: peft
license: gemma
tags:
- unsloth
- generated_from_trainer
model-index:
- name: gemma-2-9b_pct_ortho_r32
results: []
gemma-2-9b_pct_ortho_r32
This model is a fine-tuned version of google/gemma-2-9b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 9.3620
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3352 | 0.0206 | 8 | 2.9038 |
| 11.3417 | 0.0412 | 16 | 11.9083 |
| 11.9918 | 0.0618 | 24 | 11.9774 |
| 11.9549 | 0.0824 | 32 | 11.9675 |
| 11.974 | 0.1030 | 40 | 11.9736 |
| 11.9403 | 0.1236 | 48 | 11.9468 |
| 11.9321 | 0.1442 | 56 | 11.8809 |
| 11.876 | 0.1648 | 64 | 11.8218 |
| 11.7886 | 0.1854 | 72 | 11.7345 |
| 11.6471 | 0.2060 | 80 | 11.6236 |
| 11.5982 | 0.2266 | 88 | 11.3718 |
| 11.7088 | 0.2472 | 96 | 11.6792 |
| 11.7296 | 0.2678 | 104 | 11.6883 |
| 11.6508 | 0.2885 | 112 | 11.4420 |
| 10.7655 | 0.3091 | 120 | 8.8174 |
| 8.5075 | 0.3297 | 128 | 9.0568 |
| 8.912 | 0.3503 | 136 | 9.4162 |
| 11.0052 | 0.3709 | 144 | 10.3473 |
| 9.103 | 0.3915 | 152 | 9.6451 |
| 8.9631 | 0.4121 | 160 | 8.6492 |
| 9.9634 | 0.4327 | 168 | 9.4401 |
| 9.814 | 0.4533 | 176 | 10.4748 |
| 10.507 | 0.4739 | 184 | 10.1910 |
| 9.6613 | 0.4945 | 192 | 9.2201 |
| 9.0448 | 0.5151 | 200 | 10.3913 |
| 9.4984 | 0.5357 | 208 | 8.5434 |
| 7.4393 | 0.5563 | 216 | 8.4350 |
| 10.0883 | 0.5769 | 224 | 10.2584 |
| 10.7162 | 0.5975 | 232 | 10.6899 |
| 10.4785 | 0.6181 | 240 | 10.4417 |
| 10.023 | 0.6387 | 248 | 9.6244 |
| 9.2272 | 0.6593 | 256 | 8.9308 |
| 9.1518 | 0.6799 | 264 | 9.2269 |
| 9.1733 | 0.7005 | 272 | 9.2434 |
| 9.3347 | 0.7211 | 280 | 9.2831 |
| 9.468 | 0.7417 | 288 | 9.1046 |
| 8.9402 | 0.7623 | 296 | 9.0102 |
| 9.1051 | 0.7829 | 304 | 9.2617 |
| 9.2223 | 0.8035 | 312 | 9.3921 |
| 9.3359 | 0.8241 | 320 | 9.3277 |
| 9.1508 | 0.8447 | 328 | 9.2755 |
| 9.5364 | 0.8654 | 336 | 9.3031 |
| 9.4429 | 0.8860 | 344 | 9.3229 |
| 9.3958 | 0.9066 | 352 | 9.3408 |
| 9.3778 | 0.9272 | 360 | 9.3577 |
| 9.1859 | 0.9478 | 368 | 9.3607 |
| 9.4256 | 0.9684 | 376 | 9.3622 |
| 9.3454 | 0.9890 | 384 | 9.3620 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1