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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-HALF
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-HALF
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_500 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8506
- Rewards/chosen: -0.0787
- Rewards/rejected: -0.0996
- Rewards/accuracies: 0.5724
- Rewards/margins: 0.0209
- Logps/rejected: -0.9956
- Logps/chosen: -0.7867
- Logits/rejected: -3.1507
- Logits/chosen: -3.1305
- Sft Loss: 0.7867
- Odds Ratio Loss: 0.6382
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 0.8758 | 0.8467 | 500 | 0.8691 | -0.0805 | -0.1009 | 0.5705 | 0.0203 | -1.0086 | -0.8054 | -3.1276 | -3.1089 | 0.8054 | 0.6371 |
| 0.8098 | 1.6935 | 1000 | 0.8549 | -0.0791 | -0.0999 | 0.5676 | 0.0207 | -0.9985 | -0.7911 | -3.1170 | -3.0966 | 0.7911 | 0.6375 |
| 0.8135 | 2.5402 | 1500 | 0.8506 | -0.0787 | -0.0996 | 0.5724 | 0.0209 | -0.9956 | -0.7867 | -3.1507 | -3.1305 | 0.7867 | 0.6382 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |