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---
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_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue
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_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue
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: 0.1748
- Accuracy: 0.9237
## 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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7416 | 0.04 | 250 | 0.5877 | 0.7074 |
| 0.7004 | 0.08 | 500 | 0.4614 | 0.7980 |
| 0.6298 | 0.13 | 750 | 0.3453 | 0.8477 |
| 0.5979 | 0.17 | 1000 | 0.2723 | 0.8774 |
| 0.5842 | 0.21 | 1250 | 0.2469 | 0.8868 |
| 0.6257 | 0.25 | 1500 | 0.2255 | 0.8973 |
| 0.5833 | 0.29 | 1750 | 0.2103 | 0.9071 |
| 0.6368 | 0.33 | 2000 | 0.2061 | 0.9082 |
| 0.5854 | 0.38 | 2250 | 0.2063 | 0.9105 |
| 0.5458 | 0.42 | 2500 | 0.1990 | 0.9127 |
| 0.6079 | 0.46 | 2750 | 0.1993 | 0.9135 |
| 0.5819 | 0.5 | 3000 | 0.1917 | 0.9165 |
| 0.5823 | 0.54 | 3250 | 0.1844 | 0.9180 |
| 0.618 | 0.59 | 3500 | 0.1869 | 0.9188 |
| 0.6075 | 0.63 | 3750 | 0.1885 | 0.9169 |
| 0.5685 | 0.67 | 4000 | 0.1848 | 0.9191 |
| 0.5718 | 0.71 | 4250 | 0.1848 | 0.9206 |
| 0.5697 | 0.75 | 4500 | 0.1819 | 0.9210 |
| 0.5719 | 0.79 | 4750 | 0.1769 | 0.9229 |
| 0.5774 | 0.84 | 5000 | 0.1779 | 0.9218 |
| 0.5331 | 0.88 | 5250 | 0.1745 | 0.9233 |
| 0.564 | 0.92 | 5500 | 0.1752 | 0.9237 |
| 0.567 | 0.96 | 5750 | 0.1748 | 0.9237 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |