| | --- |
| | base_model: google/gemma-2b |
| | library_name: peft |
| | license: gemma |
| | metrics: |
| | - accuracy |
| | tags: |
| | - trl |
| | - reward-trainer |
| | - generated_from_trainer |
| | model-index: |
| | - name: run |
| | 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. --> |
| |
|
| | # run |
| |
|
| | This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4823 |
| | - Accuracy: 0.75 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.6406 | 0.1773 | 25 | 0.5870 | 0.6806 | |
| | | 0.5156 | 0.3546 | 50 | 0.5284 | 0.7292 | |
| | | 0.6289 | 0.5319 | 75 | 0.4963 | 0.7639 | |
| | | 0.4766 | 0.7092 | 100 | 0.4715 | 0.7639 | |
| | | 0.3594 | 0.8865 | 125 | 0.4581 | 0.7431 | |
| | | 0.4082 | 1.0638 | 150 | 0.4663 | 0.75 | |
| | | 0.3262 | 1.2411 | 175 | 0.4452 | 0.7569 | |
| | | 0.3594 | 1.4184 | 200 | 0.4306 | 0.75 | |
| | | 0.4033 | 1.5957 | 225 | 0.4411 | 0.7639 | |
| | | 0.3789 | 1.7730 | 250 | 0.4331 | 0.7708 | |
| | | 0.293 | 1.9504 | 275 | 0.4652 | 0.7569 | |
| | | 0.3555 | 2.1277 | 300 | 0.4356 | 0.7569 | |
| | | 0.4375 | 2.3050 | 325 | 0.4415 | 0.7569 | |
| | | 0.377 | 2.4823 | 350 | 0.4525 | 0.7292 | |
| | | 0.3633 | 2.6596 | 375 | 0.4505 | 0.7708 | |
| | | 0.2461 | 2.8369 | 400 | 0.4581 | 0.7431 | |
| | | 0.3115 | 3.0142 | 425 | 0.4499 | 0.7361 | |
| | | 0.3896 | 3.1915 | 450 | 0.4421 | 0.75 | |
| | | 0.373 | 3.3688 | 475 | 0.4602 | 0.7569 | |
| | | 0.2415 | 3.5461 | 500 | 0.4537 | 0.7639 | |
| | | 0.334 | 3.7234 | 525 | 0.4650 | 0.7569 | |
| | | 0.3662 | 3.9007 | 550 | 0.4750 | 0.7569 | |
| | | 0.3232 | 4.0780 | 575 | 0.4778 | 0.7361 | |
| | | 0.3369 | 4.2553 | 600 | 0.4709 | 0.75 | |
| | | 0.5273 | 4.4326 | 625 | 0.4780 | 0.75 | |
| | | 0.3623 | 4.6099 | 650 | 0.4839 | 0.75 | |
| | | 0.2148 | 4.7872 | 675 | 0.4855 | 0.7431 | |
| | | 0.3604 | 4.9645 | 700 | 0.4823 | 0.75 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.12.0 |
| | - Transformers 4.44.0 |
| | - Pytorch 2.4.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
