---
license: gemma
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: google/gemma-2b
metrics:
- accuracy
model-index:
- name: RM-HH-AllMix_helpful_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse
  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. -->

# RM-HH-AllMix_helpful_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0839
- Accuracy: 0.9876

## 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: 1.41e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7074        | 0.17  | 250  | 0.3710          | 0.8750   |
| 0.6147        | 0.33  | 500  | 0.1958          | 0.9673   |
| 0.5749        | 0.5   | 750  | 0.1424          | 0.9763   |
| 0.5776        | 0.67  | 1000 | 0.1249          | 0.9827   |
| 0.5601        | 0.84  | 1250 | 0.1087          | 0.9868   |
| 0.5549        | 1.0   | 1500 | 0.0982          | 0.9887   |
| 0.5465        | 1.17  | 1750 | 0.0941          | 0.9876   |
| 0.5494        | 1.34  | 2000 | 0.0887          | 0.9872   |
| 0.54          | 1.51  | 2250 | 0.0858          | 0.9895   |
| 0.5375        | 1.67  | 2500 | 0.0848          | 0.9891   |
| 0.5266        | 1.84  | 2750 | 0.0839          | 0.9876   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2