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---
license: mit
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi3-offline-dpo-lora-noise-0.0-5e-7-thre-1.5-42
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/causal/huggingface/runs/3pqwimtf)
# phi3-offline-dpo-lora-noise-0.0-5e-7-thre-1.5-42
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6130
- Rewards/chosen: -0.4194
- Rewards/rejected: -0.5933
- Rewards/accuracies: 0.7540
- Rewards/margins: 0.1739
- Logps/rejected: -459.6432
- Logps/chosen: -448.1436
- Logits/rejected: 12.5287
- Logits/chosen: 13.8414
## 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-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6885 | 0.1778 | 100 | 0.6884 | -0.0158 | -0.0244 | 0.6190 | 0.0086 | -402.7496 | -407.7805 | 12.8305 | 14.2621 |
| 0.6712 | 0.3556 | 200 | 0.6680 | -0.0971 | -0.1464 | 0.7937 | 0.0493 | -414.9504 | -415.9148 | 12.6482 | 14.0845 |
| 0.6339 | 0.5333 | 300 | 0.6389 | -0.2593 | -0.3712 | 0.7540 | 0.1119 | -437.4307 | -432.1300 | 12.8556 | 14.1744 |
| 0.6203 | 0.7111 | 400 | 0.6203 | -0.3738 | -0.5313 | 0.7540 | 0.1575 | -453.4457 | -443.5887 | 12.6256 | 13.9444 |
| 0.6102 | 0.8889 | 500 | 0.6131 | -0.4150 | -0.5892 | 0.7540 | 0.1743 | -459.2376 | -447.7001 | 12.5314 | 13.8427 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1 |