---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
- GaetanMichelet/chat-120_ft_task-1_auto
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-1_120-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-1_120-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 the GaetanMichelet/chat-60_ft_task-1_auto and the GaetanMichelet/chat-120_ft_task-1_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9704

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.5728        | 0.9091  | 5    | 1.6556          |
| 1.5544        | 2.0     | 11   | 1.3106          |
| 1.1135        | 2.9091  | 16   | 1.1138          |
| 0.9739        | 4.0     | 22   | 1.0347          |
| 0.8888        | 4.9091  | 27   | 0.9919          |
| 0.8107        | 6.0     | 33   | 0.9704          |
| 0.6431        | 6.9091  | 38   | 0.9726          |
| 0.5564        | 8.0     | 44   | 1.0095          |
| 0.4886        | 8.9091  | 49   | 1.1149          |
| 0.3412        | 10.0    | 55   | 1.3270          |
| 0.2372        | 10.9091 | 60   | 1.5941          |
| 0.1438        | 12.0    | 66   | 1.8735          |
| 0.0894        | 12.9091 | 71   | 2.1113          |


### Framework versions

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