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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
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
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: 1.5380
- Rewards/chosen: -0.0547
- Rewards/rejected: -0.0625
- Rewards/accuracies: 0.5468
- Rewards/margins: 0.0079
- Logps/rejected: -1.2508
- Logps/chosen: -1.0933
- Logits/rejected: 267.2346
- Logits/chosen: 296.6808
- Nll Loss: 1.4703
- Log Odds Ratio: -0.7039
- Log Odds Chosen: 0.2721
## 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: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.436 | 0.9955 | 167 | 1.4639 | -0.0502 | -0.0571 | 0.5540 | 0.0068 | -1.1413 | -1.0048 | 294.2689 | 322.9157 | 1.4152 | -0.6882 | 0.2192 |
| 1.0918 | 1.9970 | 335 | 1.4233 | -0.0501 | -0.0574 | 0.4964 | 0.0073 | -1.1475 | -1.0012 | 284.8744 | 313.3100 | 1.3661 | -0.7028 | 0.2209 |
| 0.576 | 2.9866 | 501 | 1.5380 | -0.0547 | -0.0625 | 0.5468 | 0.0079 | -1.2508 | -1.0933 | 267.2346 | 296.6808 | 1.4703 | -0.7039 | 0.2721 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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