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---
library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
- alignment-handbook
- trl
- orpo
- generated_from_trainer
- trl
- orpo
- generated_from_trainer
datasets:
- silviasapora/low_quality_dpo7k
model-index:
- name: gemma-7b-borpo-low-quality-v2
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-borpo-low-quality-v2
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the silviasapora/low_quality_dpo7k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6017
- Rewards/chosen: -0.0578
- Rewards/rejected: -0.0690
- Rewards/accuracies: 0.5714
- Rewards/margins: 0.0112
- Logps/rejected: -1.3795
- Logps/chosen: -1.1561
- Logits/rejected: 249.0934
- Logits/chosen: 304.2649
- Nll Loss: 1.5643
- Log Odds Ratio: -0.6745
- Log Odds Chosen: 0.3316
## 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-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.4218 | 1.0 | 168 | 1.4488 | -0.0504 | -0.0580 | 0.5571 | 0.0076 | -1.1591 | -1.0071 | 273.7526 | 326.8029 | 1.4553 | -0.6712 | 0.2324 |
| 1.0804 | 2.0 | 336 | 1.4225 | -0.0511 | -0.0591 | 0.5143 | 0.0080 | -1.1830 | -1.0220 | 278.2473 | 330.5067 | 1.4083 | -0.6897 | 0.2152 |
| 0.5651 | 3.0 | 504 | 1.6017 | -0.0578 | -0.0690 | 0.5714 | 0.0112 | -1.3795 | -1.1561 | 249.0934 | 304.2649 | 1.5643 | -0.6745 | 0.3316 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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