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

# outputs

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0013
- Model Preparation Time: 0.0212

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|
| 1.1766        | 0.2002 | 390  | 1.2098          | 0.0212                 |
| 1.2063        | 0.4003 | 780  | 1.1293          | 0.0212                 |
| 1.063         | 0.6005 | 1170 | 1.0843          | 0.0212                 |
| 1.0623        | 0.8006 | 1560 | 1.0545          | 0.0212                 |
| 0.9728        | 1.0008 | 1950 | 1.0336          | 0.0212                 |
| 0.9455        | 1.2009 | 2340 | 1.0228          | 0.0212                 |
| 1.0184        | 1.4011 | 2730 | 1.0115          | 0.0212                 |
| 0.9698        | 1.6012 | 3120 | 1.0042          | 0.0212                 |
| 0.935         | 1.8014 | 3510 | 1.0013          | 0.0212                 |


### Framework versions

- PEFT 0.13.1
- Transformers 4.45.2
- Pytorch 2.2.1
- Datasets 3.0.1
- Tokenizers 0.20.1