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---
license: apache-2.0
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.3
model-index:
- name: Mistral-7B-Instruct-v0.3-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. -->
# Mistral-7B-Instruct-v0.3-ORPO-SALT
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8434
- Rewards/chosen: -0.0777
- Rewards/rejected: -0.0988
- Rewards/accuracies: 0.5691
- Rewards/margins: 0.0210
- Logps/rejected: -0.9877
- Logps/chosen: -0.7773
- Logits/rejected: -3.1073
- Logits/chosen: -3.0834
- Sft Loss: 0.7773
- Odds Ratio Loss: 0.6614
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 0.8803 | 0.8082 | 500 | 0.8619 | -0.0796 | -0.0983 | 0.5655 | 0.0187 | -0.9834 | -0.7962 | -3.0746 | -3.0520 | 0.7962 | 0.6572 |
| 0.7341 | 1.6165 | 1000 | 0.8450 | -0.0779 | -0.0980 | 0.5673 | 0.0201 | -0.9804 | -0.7795 | -3.1194 | -3.0960 | 0.7795 | 0.6550 |
| 0.7691 | 2.4247 | 1500 | 0.8434 | -0.0777 | -0.0988 | 0.5691 | 0.0210 | -0.9877 | -0.7773 | -3.1073 | -3.0834 | 0.7773 | 0.6614 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |