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---
license: gemma
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: google/gemma-2b-it
model-index:
- name: Gemma-2B-It-ORPO-SALT
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-2B-It-ORPO-SALT
This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co./google/gemma-2b-it) on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.3294
- Rewards/chosen: -0.1257
- Rewards/rejected: -0.1400
- Rewards/accuracies: 0.5345
- Rewards/margins: 0.0142
- Logps/rejected: -1.3996
- Logps/chosen: -1.2573
- Logits/rejected: -20.6959
- Logits/chosen: -20.6644
- Sft Loss: 1.2573
- Odds Ratio Loss: 0.7207
## 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: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.4057 | 0.8082 | 500 | 1.3871 | -0.1315 | -0.1452 | 0.5318 | 0.0137 | -1.4522 | -1.3148 | -21.9402 | -21.9144 | 1.3148 | 0.7223 |
| 1.2196 | 1.6165 | 1000 | 1.3397 | -0.1268 | -0.1408 | 0.5355 | 0.0140 | -1.4079 | -1.2678 | -20.9111 | -20.8823 | 1.2678 | 0.7187 |
| 1.2883 | 2.4247 | 1500 | 1.3294 | -0.1257 | -0.1400 | 0.5345 | 0.0142 | -1.3996 | -1.2573 | -20.6959 | -20.6644 | 1.2573 | 0.7207 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |