---
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-2_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-2_60-samples_config-2_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: 0.8866

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 0.9552        | 0.6957  | 2    | 1.0746          |
| 0.9555        | 1.7391  | 5    | 1.0326          |
| 0.8712        | 2.7826  | 8    | 0.9149          |
| 0.7712        | 3.8261  | 11   | 0.8319          |
| 0.6958        | 4.8696  | 14   | 0.7876          |
| 0.6428        | 5.9130  | 17   | 0.7529          |
| 0.5843        | 6.9565  | 20   | 0.7262          |
| 0.561         | 8.0     | 23   | 0.7111          |
| 0.5211        | 8.6957  | 25   | 0.7022          |
| 0.456         | 9.7391  | 28   | 0.6938          |
| 0.4502        | 10.7826 | 31   | 0.6950          |
| 0.3993        | 11.8261 | 34   | 0.7011          |
| 0.3589        | 12.8696 | 37   | 0.7186          |
| 0.3157        | 13.9130 | 40   | 0.7445          |
| 0.2717        | 14.9565 | 43   | 0.7838          |
| 0.2344        | 16.0    | 46   | 0.8412          |
| 0.1863        | 16.6957 | 48   | 0.8866          |


### Framework versions

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