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---
license: gemma
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
base_model: google/gemma-2b
model-index:
- name: RM-HH-Mix_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-Mix_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: 0.1257
- Accuracy: 0.9465
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8425 | 0.06 | 250 | 0.8667 | 0.5565 |
| 0.7359 | 0.11 | 500 | 0.5129 | 0.774 |
| 0.6491 | 0.17 | 750 | 0.3182 | 0.8645 |
| 0.6171 | 0.22 | 1000 | 0.2427 | 0.904 |
| 0.5956 | 0.28 | 1250 | 0.1885 | 0.925 |
| 0.5504 | 0.33 | 1500 | 0.1771 | 0.928 |
| 0.5778 | 0.39 | 1750 | 0.1663 | 0.931 |
| 0.574 | 0.44 | 2000 | 0.1533 | 0.937 |
| 0.614 | 0.5 | 2250 | 0.1523 | 0.9355 |
| 0.5568 | 0.56 | 2500 | 0.1427 | 0.9395 |
| 0.5474 | 0.61 | 2750 | 0.1300 | 0.9435 |
| 0.5179 | 0.67 | 3000 | 0.1308 | 0.944 |
| 0.5643 | 0.72 | 3250 | 0.1231 | 0.947 |
| 0.5704 | 0.78 | 3500 | 0.1262 | 0.9465 |
| 0.5348 | 0.83 | 3750 | 0.1275 | 0.946 |
| 0.5388 | 0.89 | 4000 | 0.1256 | 0.947 |
| 0.5579 | 0.94 | 4250 | 0.1257 | 0.9465 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2 |