---
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_120-samples_config-2_full_auto
  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_120-samples_config-2_full_auto

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: 1.0821

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.4057        | 0.9091  | 5    | 1.3750          |
| 1.3708        | 2.0     | 11   | 1.2889          |
| 1.2158        | 2.9091  | 16   | 1.1944          |
| 1.1179        | 4.0     | 22   | 1.1044          |
| 1.0198        | 4.9091  | 27   | 1.0251          |
| 0.9467        | 6.0     | 33   | 0.9804          |
| 0.9148        | 6.9091  | 38   | 0.9615          |
| 0.8909        | 8.0     | 44   | 0.9481          |
| 0.8645        | 8.9091  | 49   | 0.9407          |
| 0.867         | 10.0    | 55   | 0.9363          |
| 0.8193        | 10.9091 | 60   | 0.9359          |
| 0.7911        | 12.0    | 66   | 0.9404          |
| 0.7557        | 12.9091 | 71   | 0.9464          |
| 0.7439        | 14.0    | 77   | 0.9614          |
| 0.6475        | 14.9091 | 82   | 0.9828          |
| 0.6577        | 16.0    | 88   | 1.0100          |
| 0.5958        | 16.9091 | 93   | 1.0415          |
| 0.5391        | 18.0    | 99   | 1.0821          |


### Framework versions

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