---
license: gemma
base_model: google/gemma-2-2b
tags:
- easylm
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- alpaca_farm
model-index:
- name: easylm-sft-gemma-2-2b
  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. -->

# easylm-sft-gemma-2-2b

This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on the alpaca_farm dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7072

## 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: 3e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6727        | 0.16  | 100  | 0.6869          |
| 0.6056        | 0.32  | 200  | 0.6831          |
| 0.7033        | 0.48  | 300  | 0.6797          |
| 0.6786        | 0.64  | 400  | 0.6771          |
| 0.6476        | 0.8   | 500  | 0.6736          |
| 0.6562        | 0.96  | 600  | 0.6708          |
| 0.461         | 1.12  | 700  | 0.7041          |
| 0.4578        | 1.28  | 800  | 0.7093          |
| 0.4817        | 1.44  | 900  | 0.7055          |
| 0.4324        | 1.6   | 1000 | 0.7080          |
| 0.4693        | 1.76  | 1100 | 0.7081          |
| 0.4475        | 1.92  | 1200 | 0.7070          |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1