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---
license: other
base_model: lewtun/gemma-7b-sft-full-deita-10k-v0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
- HuggingFaceH4/orca_dpo_pairs
model-index:
- name: gemma-7b-dpo-full-mix2-beta-0.1
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. -->
# gemma-7b-dpo-full-mix2-beta-0.1
This model is a fine-tuned version of [lewtun/gemma-7b-sft-full-deita-10k-v0](https://huggingface.co/lewtun/gemma-7b-sft-full-deita-10k-v0) on the HuggingFaceH4/ultrafeedback_binarized and the HuggingFaceH4/orca_dpo_pairs datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4056
- Rewards/chosen: -0.3995
- Rewards/rejected: -3.5721
- Rewards/accuracies: 0.7926
- Rewards/margins: 3.1726
- Logps/rejected: -414.5198
- Logps/chosen: -392.3416
- Logits/rejected: 83.8425
- Logits/chosen: 83.1641
## 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: 5e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6146 | 0.18 | 100 | 0.4651 | -2.3366 | -4.2121 | 0.7527 | 1.8755 | -420.9197 | -411.7124 | 84.3991 | 81.8795 |
| 0.5464 | 0.35 | 200 | 0.4531 | -0.7850 | -3.1857 | 0.7899 | 2.4007 | -410.6562 | -396.1968 | 84.8764 | 82.9057 |
| 0.5841 | 0.53 | 300 | 0.4209 | -1.5926 | -4.2403 | 0.8085 | 2.6477 | -421.2023 | -404.2725 | 83.7612 | 81.9224 |
| 0.519 | 0.7 | 400 | 0.4162 | -1.2384 | -4.1774 | 0.7819 | 2.9390 | -420.5732 | -400.7308 | 85.8201 | 84.7816 |
| 0.5432 | 0.88 | 500 | 0.4134 | -0.3763 | -3.5060 | 0.8032 | 3.1296 | -413.8586 | -392.1099 | 83.6363 | 82.8991 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1
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