---
base_model: google/gemma-2-2b-it
library_name: peft
license: gemma
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-3_180-samples_config-2_full
  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. -->

# Gemma-2-2B_task-3_180-samples_config-2_full

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: 1.1691

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.3981        | 0.9412  | 8    | 1.3785          |
| 1.3072        | 2.0     | 17   | 1.2429          |
| 1.1985        | 2.9412  | 25   | 1.1442          |
| 0.9971        | 4.0     | 34   | 1.0312          |
| 0.9268        | 4.9412  | 42   | 0.9882          |
| 0.9442        | 6.0     | 51   | 0.9653          |
| 0.9253        | 6.9412  | 59   | 0.9537          |
| 0.8684        | 8.0     | 68   | 0.9479          |
| 0.8043        | 8.9412  | 76   | 0.9456          |
| 0.7924        | 10.0    | 85   | 0.9502          |
| 0.7535        | 10.9412 | 93   | 0.9591          |
| 0.694         | 12.0    | 102  | 0.9863          |
| 0.6881        | 12.9412 | 110  | 0.9994          |
| 0.6566        | 14.0    | 119  | 1.0534          |
| 0.5597        | 14.9412 | 127  | 1.1117          |
| 0.497         | 16.0    | 136  | 1.1691          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1