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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_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 |