| | --- |
| | library_name: transformers |
| | license: gemma |
| | base_model: google/gemma-2-9b |
| | tags: |
| | - llama-factory |
| | - full |
| | - generated_from_trainer |
| | model-index: |
| | - name: hp_ablations_gemma_bsz256 |
| | 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. --> |
| |
|
| | # hp_ablations_gemma_bsz256 |
| | |
| | This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the mlfoundations-dev/oh-dcft-v3.1-gpt-4o-mini dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6163 |
| | |
| | ## 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: 5e-06 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 8 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 256 |
| | - total_eval_batch_size: 32 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: constant |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - lr_scheduler_warmup_steps: 1738 |
| | - num_epochs: 3.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.5875 | 0.9997 | 886 | 0.5917 | |
| | | 0.5215 | 1.9994 | 1772 | 0.5914 | |
| | | 0.4672 | 2.9992 | 2658 | 0.6163 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.1 |
| | - Pytorch 2.3.0 |
| | - Datasets 3.0.2 |
| | - Tokenizers 0.20.3 |
| | |
