---
library_name: peft
license: mit
base_model: fxmarty/tiny-random-GemmaForCausalLM
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 09562065-19e2-4296-812c-7420d36612d2
  results: []
---

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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# 09562065-19e2-4296-812c-7420d36612d2

This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 12.3853

## 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: 0.000218
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0010 | 1    | 12.4603         |
| 12.4566       | 0.0498 | 50   | 12.4551         |
| 12.4036       | 0.0996 | 100  | 12.3979         |
| 12.3863       | 0.1493 | 150  | 12.3890         |
| 12.3915       | 0.1991 | 200  | 12.3869         |
| 12.3782       | 0.2489 | 250  | 12.3859         |
| 12.383        | 0.2987 | 300  | 12.3853         |
| 12.3854       | 0.3484 | 350  | 12.3855         |
| 12.3848       | 0.3982 | 400  | 12.3853         |
| 12.3851       | 0.4480 | 450  | 12.3852         |
| 12.3824       | 0.4978 | 500  | 12.3853         |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1