---
library_name: peft
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: gemma2-mentalchat16k
  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. -->

# gemma2-mentalchat16k

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7946

## 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: 0.0002
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0076        | 0.1122 | 100  | 0.9827          |
| 0.9399        | 0.2243 | 200  | 0.9345          |
| 0.9054        | 0.3365 | 300  | 0.9031          |
| 0.8561        | 0.4487 | 400  | 0.8859          |
| 0.8794        | 0.5609 | 500  | 0.8711          |
| 0.844         | 0.6730 | 600  | 0.8557          |
| 0.8305        | 0.7852 | 700  | 0.8461          |
| 0.8207        | 0.8974 | 800  | 0.8400          |
| 0.8117        | 1.0090 | 900  | 0.8529          |
| 0.7338        | 1.1211 | 1000 | 0.8448          |
| 0.7422        | 1.2333 | 1100 | 0.8332          |
| 0.6964        | 1.3455 | 1200 | 0.8273          |
| 0.7064        | 1.4577 | 1300 | 0.8252          |
| 0.7201        | 1.5698 | 1400 | 0.8170          |
| 0.7162        | 1.6820 | 1500 | 0.8121          |
| 0.688         | 1.7942 | 1600 | 0.8088          |
| 0.7166        | 1.9063 | 1700 | 0.7998          |
| 0.636         | 2.0179 | 1800 | 0.8447          |
| 0.5388        | 2.1301 | 1900 | 0.8485          |
| 0.5319        | 2.2423 | 2000 | 0.8444          |
| 0.5396        | 2.3545 | 2100 | 0.8498          |
| 0.5523        | 2.4666 | 2200 | 0.8446          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.54.1
- Pytorch 2.7.1+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1