---
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-2_60-samples_config-1_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-2_60-samples_config-1_full

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1345

## 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: 8
- total_train_batch_size: 8
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.2928        | 0.8696  | 5    | 1.3069          |
| 1.2992        | 1.9130  | 11   | 1.2225          |
| 1.1839        | 2.9565  | 17   | 1.1170          |
| 1.0415        | 4.0     | 23   | 1.0408          |
| 0.9451        | 4.8696  | 28   | 0.9726          |
| 0.8679        | 5.9130  | 34   | 0.9312          |
| 0.8006        | 6.9565  | 40   | 0.9111          |
| 0.7924        | 8.0     | 46   | 0.9005          |
| 0.7768        | 8.8696  | 51   | 0.8965          |
| 0.7665        | 9.9130  | 57   | 0.8953          |
| 0.6893        | 10.9565 | 63   | 0.9024          |
| 0.6515        | 12.0    | 69   | 0.9145          |
| 0.6535        | 12.8696 | 74   | 0.9321          |
| 0.5737        | 13.9130 | 80   | 0.9723          |
| 0.5352        | 14.9565 | 86   | 0.9994          |
| 0.5419        | 16.0    | 92   | 1.0520          |
| 0.3587        | 16.8696 | 97   | 1.1345          |


### Framework versions

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