run-gemma
This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4238
- Accuracy: 0.7778
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7031 | 0.1087 | 10 | 0.6740 | 0.5752 |
| 0.6719 | 0.2174 | 20 | 0.6701 | 0.6046 |
| 0.6602 | 0.3261 | 30 | 0.6497 | 0.6601 |
| 0.6367 | 0.4348 | 40 | 0.6113 | 0.7059 |
| 0.6172 | 0.5435 | 50 | 0.5686 | 0.7320 |
| 0.5625 | 0.6522 | 60 | 0.5276 | 0.7451 |
| 0.5664 | 0.7609 | 70 | 0.4938 | 0.7451 |
| 0.5859 | 0.8696 | 80 | 0.4651 | 0.7712 |
| 0.5 | 0.9783 | 90 | 0.4560 | 0.7647 |
| 0.5898 | 1.0870 | 100 | 0.4560 | 0.7582 |
| 0.5664 | 1.1957 | 110 | 0.4459 | 0.7516 |
| 0.4648 | 1.3043 | 120 | 0.4387 | 0.7745 |
| 0.5117 | 1.4130 | 130 | 0.4306 | 0.7712 |
| 0.4219 | 1.5217 | 140 | 0.4239 | 0.7680 |
| 0.3828 | 1.6304 | 150 | 0.4314 | 0.7680 |
| 0.3789 | 1.7391 | 160 | 0.4319 | 0.7647 |
| 0.3828 | 1.8478 | 170 | 0.4291 | 0.7680 |
| 0.3438 | 1.9565 | 180 | 0.4279 | 0.7745 |
| 0.3496 | 2.0652 | 190 | 0.4274 | 0.7712 |
| 0.3945 | 2.1739 | 200 | 0.4238 | 0.7778 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1