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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-v3
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-v3
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: 2.1095
- Rewards/chosen: -0.6954
- Rewards/rejected: -0.8346
- Rewards/accuracies: 0.5571
- Rewards/margins: 0.1392
- Logps/rejected: -1.6692
- Logps/chosen: -1.3909
- Logits/rejected: 262.5518
- Logits/chosen: 319.3429
- Nll Loss: 1.7836
- Log Odds Ratio: -0.6395
- Log Odds Chosen: 0.4455
## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.9721 | 1.0 | 168 | 1.9526 | -0.6072 | -0.7027 | 0.5571 | 0.0955 | -1.4054 | -1.2144 | 282.1215 | 336.2867 | 1.6515 | -0.6573 | 0.2649 |
| 1.3299 | 2.0 | 336 | 1.9015 | -0.5986 | -0.6805 | 0.5 | 0.0820 | -1.3611 | -1.1972 | 293.2820 | 345.2333 | 1.5933 | -0.6792 | 0.2173 |
| 0.6266 | 3.0 | 504 | 2.1095 | -0.6954 | -0.8346 | 0.5571 | 0.1392 | -1.6692 | -1.3909 | 262.5518 | 319.3429 | 1.7836 | -0.6395 | 0.4455 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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