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---
base_model: google/gemma-2b
library_name: peft
license: gemma
metrics:
- accuracy
tags:
- trl
- reward-trainer
- generated_from_trainer
model-index:
- name: reward_modeling
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/quirky_lats_at_mats/huggingface/runs/k92pr3b1)
# reward_modeling
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4036
- Accuracy: 0.8058
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9241 | 0.0787 | 5 | 0.6996 | 0.5678 |
| 0.7708 | 0.1575 | 10 | 0.6284 | 0.6660 |
| 0.7875 | 0.2362 | 15 | 0.5749 | 0.7244 |
| 0.6575 | 0.3150 | 20 | 0.5360 | 0.7390 |
| 0.6802 | 0.3937 | 25 | 0.5087 | 0.7432 |
| 0.3982 | 0.4724 | 30 | 0.4890 | 0.7578 |
| 0.4555 | 0.5512 | 35 | 0.4775 | 0.7599 |
| 0.8838 | 0.6299 | 40 | 0.4683 | 0.7662 |
| 0.4692 | 0.7087 | 45 | 0.4611 | 0.7662 |
| 0.5455 | 0.7874 | 50 | 0.4531 | 0.7620 |
| 0.5696 | 0.8661 | 55 | 0.4459 | 0.7662 |
| 0.7453 | 0.9449 | 60 | 0.4414 | 0.7766 |
| 0.5369 | 1.0236 | 65 | 0.4371 | 0.7829 |
| 0.3994 | 1.1024 | 70 | 0.4334 | 0.7850 |
| 0.4235 | 1.1811 | 75 | 0.4298 | 0.7912 |
| 0.4811 | 1.2598 | 80 | 0.4266 | 0.7912 |
| 0.5072 | 1.3386 | 85 | 0.4253 | 0.7912 |
| 0.4405 | 1.4173 | 90 | 0.4228 | 0.7850 |
| 0.5349 | 1.4961 | 95 | 0.4196 | 0.7871 |
| 0.3342 | 1.5748 | 100 | 0.4170 | 0.7829 |
| 0.5271 | 1.6535 | 105 | 0.4149 | 0.7933 |
| 0.3463 | 1.7323 | 110 | 0.4136 | 0.7975 |
| 0.4867 | 1.8110 | 115 | 0.4128 | 0.7996 |
| 0.3221 | 1.8898 | 120 | 0.4125 | 0.7996 |
| 0.3542 | 1.9685 | 125 | 0.4116 | 0.7996 |
| 0.5465 | 2.0472 | 130 | 0.4107 | 0.7996 |
| 0.3427 | 2.1260 | 135 | 0.4101 | 0.7996 |
| 0.4787 | 2.2047 | 140 | 0.4087 | 0.8038 |
| 0.4229 | 2.2835 | 145 | 0.4073 | 0.8017 |
| 0.4514 | 2.3622 | 150 | 0.4063 | 0.8038 |
| 0.5116 | 2.4409 | 155 | 0.4051 | 0.8038 |
| 0.3234 | 2.5197 | 160 | 0.4045 | 0.8058 |
| 0.3993 | 2.5984 | 165 | 0.4040 | 0.8058 |
| 0.3264 | 2.6772 | 170 | 0.4037 | 0.8058 |
| 0.3316 | 2.7559 | 175 | 0.4035 | 0.8038 |
| 0.4855 | 2.8346 | 180 | 0.4035 | 0.8038 |
| 0.536 | 2.9134 | 185 | 0.4036 | 0.8058 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |