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---
library_name: peft
license: gemma
base_model: unsloth/gemma-2-2b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5a4bf373-7928-4fea-aea6-2b0160f5d1c9
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. -->
[<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>
# 5a4bf373-7928-4fea-aea6-2b0160f5d1c9
This model is a fine-tuned version of [unsloth/gemma-2-2b](https://huggingface.co/unsloth/gemma-2-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3595
## 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: 0.00021
- train_batch_size: 4
- eval_batch_size: 4
- seed: 100
- 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 | 0.0000 | 1 | 1.6350 |
| 1.3774 | 0.0008 | 50 | 1.4623 |
| 1.3825 | 0.0017 | 100 | 1.4445 |
| 1.3845 | 0.0025 | 150 | 1.4355 |
| 1.2979 | 0.0033 | 200 | 1.4278 |
| 1.3492 | 0.0041 | 250 | 1.4065 |
| 1.2435 | 0.0050 | 300 | 1.3964 |
| 1.2813 | 0.0058 | 350 | 1.3751 |
| 1.3393 | 0.0066 | 400 | 1.3661 |
| 1.3273 | 0.0075 | 450 | 1.3599 |
| 1.2704 | 0.0083 | 500 | 1.3595 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1 |