metadata
base_model: google/gemma-2-9b
library_name: peft
license: gemma
tags:
- unsloth
- generated_from_trainer
model-index:
- name: gemma-2-9b_pct_reverse_r32
results: []
gemma-2-9b_pct_reverse_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: 9.9020
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 |
|---|---|---|---|
| 2.5978 | 0.0206 | 8 | 4.9799 |
| 11.0056 | 0.0412 | 16 | 11.4640 |
| 11.7215 | 0.0618 | 24 | 11.8765 |
| 11.8793 | 0.0824 | 32 | 11.9059 |
| 11.8739 | 0.1030 | 40 | 11.9781 |
| 11.8763 | 0.1236 | 48 | 11.9487 |
| 11.8231 | 0.1442 | 56 | 11.8282 |
| 11.7758 | 0.1648 | 64 | 11.7664 |
| 11.8011 | 0.1854 | 72 | 11.4372 |
| 11.6991 | 0.2060 | 80 | 11.7334 |
| 11.8108 | 0.2266 | 88 | 11.5005 |
| 11.6519 | 0.2472 | 96 | 11.5944 |
| 11.6905 | 0.2678 | 104 | 11.5944 |
| 11.6003 | 0.2885 | 112 | 11.5914 |
| 11.5813 | 0.3091 | 120 | 11.5684 |
| 11.5493 | 0.3297 | 128 | 11.7560 |
| 11.5458 | 0.3503 | 136 | 11.4566 |
| 11.5838 | 0.3709 | 144 | 11.4331 |
| 11.4815 | 0.3915 | 152 | 11.5174 |
| 11.5369 | 0.4121 | 160 | 11.5271 |
| 11.4617 | 0.4327 | 168 | 11.5392 |
| 11.4399 | 0.4533 | 176 | 11.3691 |
| 11.3199 | 0.4739 | 184 | 10.9823 |
| 10.6547 | 0.4945 | 192 | 10.0666 |
| 8.8163 | 0.5151 | 200 | 8.7638 |
| 9.5635 | 0.5357 | 208 | 8.5153 |
| 8.7862 | 0.5563 | 216 | 9.2186 |
| 10.2774 | 0.5769 | 224 | 10.3834 |
| 9.7932 | 0.5975 | 232 | 9.7972 |
| 9.5421 | 0.6181 | 240 | 9.6845 |
| 9.5401 | 0.6387 | 248 | 9.3438 |
| 10.9001 | 0.6593 | 256 | 10.6070 |
| 9.959 | 0.6799 | 264 | 9.6172 |
| 9.5409 | 0.7005 | 272 | 10.4762 |
| 10.8074 | 0.7211 | 280 | 10.4872 |
| 9.1645 | 0.7417 | 288 | 7.6567 |
| 8.1072 | 0.7623 | 296 | 8.7911 |
| 9.7069 | 0.7829 | 304 | 10.0043 |
| 10.0752 | 0.8035 | 312 | 10.1655 |
| 9.9734 | 0.8241 | 320 | 9.9644 |
| 9.6722 | 0.8447 | 328 | 9.7803 |
| 9.8279 | 0.8654 | 336 | 9.5826 |
| 9.6714 | 0.8860 | 344 | 9.5533 |
| 9.655 | 0.9066 | 352 | 9.6339 |
| 9.7184 | 0.9272 | 360 | 9.7651 |
| 9.6142 | 0.9478 | 368 | 9.8536 |
| 9.9249 | 0.9684 | 376 | 9.8906 |
| 9.8654 | 0.9890 | 384 | 9.9020 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1