| --- |
| library_name: peft |
| license: gemma |
| base_model: google/gemma-2-9b |
| tags: |
| - base_model:adapter:google/gemma-2-9b |
| - lora |
| - transformers |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: google_gemma-2-9b_StereoDetect_Model |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # google_gemma-2-9b_StereoDetect_Model |
| |
| This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2997 |
| - Accuracy: 0.9505 |
| - Balanced Accuracy: 0.9501 |
| - F1 Weighted: 0.9508 |
| - F1 Macro: 0.9513 |
| - Precision: 0.9517 |
| - Recall: 0.9505 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | F1 Weighted | F1 Macro | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:-----------:|:--------:|:---------:|:------:| |
| | 0.9444 | 1.0 | 760 | 0.3210 | 0.9217 | 0.9227 | 0.9225 | 0.9223 | 0.9239 | 0.9217 | |
| | 0.2271 | 2.0 | 1520 | 0.2235 | 0.9459 | 0.9459 | 0.9462 | 0.9461 | 0.9467 | 0.9459 | |
| | 0.1214 | 3.0 | 2280 | 0.2020 | 0.9516 | 0.9513 | 0.9518 | 0.9522 | 0.9525 | 0.9516 | |
| | 0.0705 | 4.0 | 3040 | 0.2116 | 0.9505 | 0.9499 | 0.9506 | 0.9511 | 0.9512 | 0.9505 | |
| | 0.0376 | 5.0 | 3800 | 0.2778 | 0.9470 | 0.9469 | 0.9474 | 0.9479 | 0.9480 | 0.9470 | |
| | 0.025 | 6.0 | 4560 | 0.2502 | 0.9551 | 0.9547 | 0.9554 | 0.9556 | 0.9558 | 0.9551 | |
| | 0.0099 | 7.0 | 5320 | 0.3018 | 0.9505 | 0.9502 | 0.9508 | 0.9512 | 0.9514 | 0.9505 | |
| | 0.013 | 8.0 | 6080 | 0.2715 | 0.9482 | 0.9480 | 0.9485 | 0.9490 | 0.9493 | 0.9482 | |
| | 0.0073 | 9.0 | 6840 | 0.2916 | 0.9516 | 0.9515 | 0.9519 | 0.9522 | 0.9526 | 0.9516 | |
| | 0.0027 | 10.0 | 7600 | 0.2997 | 0.9505 | 0.9501 | 0.9508 | 0.9513 | 0.9517 | 0.9505 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.19.1 |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 4.8.5 |
| - Tokenizers 0.21.4 |
