---
license: gemma
base_model: google/gemma-2-2b-it
tags:
- easylm
- alignment-handbook
- trl
- reward-trainer
- generated_from_trainer
datasets:
- helpsteer-rm
metrics:
- accuracy
model-index:
- name: easylm-helpsteer-rm-gemma-2-2b-it
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: helpsteer-rm
      type: helpsteer-rm
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.653179190751445
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# easylm-helpsteer-rm-gemma-2-2b-it

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the helpsteer-rm dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6647
- Accuracy: 0.6532

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 3
- total_eval_batch_size: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.711         | 0.4579 | 1000 | 0.7638          | 0.6214   |
| 0.6407        | 0.9158 | 2000 | 0.6655          | 0.6329   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1