---
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_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-2_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: 0.9127

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.2929        | 0.6957  | 2    | 1.3116          |
| 1.3056        | 1.7391  | 5    | 1.2842          |
| 1.2411        | 2.7826  | 8    | 1.1890          |
| 1.1401        | 3.8261  | 11   | 1.1172          |
| 1.0766        | 4.8696  | 14   | 1.0738          |
| 1.024         | 5.9130  | 17   | 1.0270          |
| 0.9524        | 6.9565  | 20   | 0.9851          |
| 0.9285        | 8.0     | 23   | 0.9539          |
| 0.8884        | 8.6957  | 25   | 0.9410          |
| 0.8534        | 9.7391  | 28   | 0.9267          |
| 0.8501        | 10.7826 | 31   | 0.9164          |
| 0.8295        | 11.8261 | 34   | 0.9091          |
| 0.7979        | 12.8696 | 37   | 0.9039          |
| 0.796         | 13.9130 | 40   | 0.9001          |
| 0.7651        | 14.9565 | 43   | 0.8977          |
| 0.769         | 16.0    | 46   | 0.8965          |
| 0.733         | 16.6957 | 48   | 0.8957          |
| 0.743         | 17.7391 | 51   | 0.8961          |
| 0.7346        | 18.7826 | 54   | 0.8963          |
| 0.7113        | 19.8261 | 57   | 0.8982          |
| 0.7027        | 20.8696 | 60   | 0.9012          |
| 0.6939        | 21.9130 | 63   | 0.9043          |
| 0.6772        | 22.9565 | 66   | 0.9081          |
| 0.6706        | 24.0    | 69   | 0.9127          |


### Framework versions

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