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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_shuffleTrue_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_harmless_gpt3_20000_gemma2b_shuffleTrue_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: 0.5035
- Accuracy: 0.7281
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6954 | 0.04 | 250 | 0.6616 | 0.5961 |
| 0.6049 | 0.08 | 500 | 0.5946 | 0.6491 |
| 0.559 | 0.13 | 750 | 0.5750 | 0.6657 |
| 0.5508 | 0.17 | 1000 | 0.5561 | 0.6800 |
| 0.5562 | 0.21 | 1250 | 0.5426 | 0.6886 |
| 0.5167 | 0.25 | 1500 | 0.5325 | 0.6916 |
| 0.5202 | 0.29 | 1750 | 0.5269 | 0.7029 |
| 0.4852 | 0.33 | 2000 | 0.5255 | 0.7070 |
| 0.4796 | 0.38 | 2250 | 0.5265 | 0.7093 |
| 0.5037 | 0.42 | 2500 | 0.5196 | 0.7119 |
| 0.4928 | 0.46 | 2750 | 0.5221 | 0.7146 |
| 0.5138 | 0.5 | 3000 | 0.5257 | 0.7206 |
| 0.4909 | 0.54 | 3250 | 0.5216 | 0.7202 |
| 0.5197 | 0.59 | 3500 | 0.5130 | 0.7273 |
| 0.5086 | 0.63 | 3750 | 0.5107 | 0.7277 |
| 0.5366 | 0.67 | 4000 | 0.5075 | 0.7281 |
| 0.5121 | 0.71 | 4250 | 0.5043 | 0.7292 |
| 0.4945 | 0.75 | 4500 | 0.5048 | 0.7285 |
| 0.5112 | 0.79 | 4750 | 0.5039 | 0.7303 |
| 0.4971 | 0.84 | 5000 | 0.5022 | 0.7300 |
| 0.5118 | 0.88 | 5250 | 0.5031 | 0.7285 |
| 0.4899 | 0.92 | 5500 | 0.5029 | 0.7288 |
| 0.4671 | 0.96 | 5750 | 0.5035 | 0.7281 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |