---
library_name: transformers
license: gemma
base_model: google/gemma-2-9b
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: hp_ablations_gemma_scheduler_linear_warmup0.05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hp_ablations_gemma_scheduler_linear_warmup0.05

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: 0.5897

## 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: 16
- total_train_batch_size: 512
- 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: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5938        | 0.9997 | 443  | 0.5919          |
| 0.5447        | 1.9994 | 886  | 0.5841          |
| 0.4998        | 2.9992 | 1329 | 0.5897          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.0.2
- Tokenizers 0.20.3