---
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_60-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_60-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9809

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.3458        | 0.6957  | 2    | 1.3568          |
| 1.3656        | 1.7391  | 5    | 1.3315          |
| 1.3043        | 2.7826  | 8    | 1.2450          |
| 1.2137        | 3.8261  | 11   | 1.1760          |
| 1.1349        | 4.8696  | 14   | 1.1266          |
| 1.0892        | 5.9130  | 17   | 1.0786          |
| 1.0063        | 6.9565  | 20   | 1.0362          |
| 0.9866        | 8.0     | 23   | 1.0086          |
| 0.9437        | 8.6957  | 25   | 0.9958          |
| 0.9105        | 9.7391  | 28   | 0.9805          |
| 0.9086        | 10.7826 | 31   | 0.9711          |
| 0.884         | 11.8261 | 34   | 0.9645          |
| 0.852         | 12.8696 | 37   | 0.9601          |
| 0.8465        | 13.9130 | 40   | 0.9575          |
| 0.8197        | 14.9565 | 43   | 0.9567          |
| 0.8147        | 16.0    | 46   | 0.9571          |
| 0.7741        | 16.6957 | 48   | 0.9576          |
| 0.7843        | 17.7391 | 51   | 0.9597          |
| 0.7714        | 18.7826 | 54   | 0.9630          |
| 0.7444        | 19.8261 | 57   | 0.9685          |
| 0.7328        | 20.8696 | 60   | 0.9758          |
| 0.7226        | 21.9130 | 63   | 0.9809          |


### Framework versions

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