---
base_model: rasyosef/phi-2-sft-openhermes-128k-v2-merged
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: phi-2-apo
  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. -->

# phi-2-apo

This model is a fine-tuned version of [rasyosef/phi-2-sft-openhermes-128k-v2-merged](https://huggingface.co/rasyosef/phi-2-sft-openhermes-128k-v2-merged) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3695
- Rewards/chosen: 1.5931
- Rewards/rejected: -3.0842
- Rewards/accuracies: 0.9350
- Rewards/margins: 4.6772
- Logps/rejected: -173.1941
- Logps/chosen: -253.6105
- Logits/rejected: -0.4322
- Logits/chosen: 0.1424

## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3669        | 0.2041 | 250  | 0.3828          | 1.5010         | -2.9712          | 0.9450             | 4.4722          | -172.0644      | -254.5310    | -0.4930         | 0.0860        |
| 0.3514        | 0.4082 | 500  | 0.3786          | 1.5375         | -2.9788          | 0.9400             | 4.5163          | -172.1404      | -254.1665    | -0.4834         | 0.0968        |
| 0.3539        | 0.6122 | 750  | 0.3756          | 1.5549         | -3.0097          | 0.9400             | 4.5647          | -172.4500      | -253.9920    | -0.4690         | 0.1096        |
| 0.3562        | 0.8163 | 1000 | 0.3736          | 1.5759         | -3.0081          | 0.9450             | 4.5840          | -172.4332      | -253.7824    | -0.4558         | 0.1220        |
| 0.3437        | 1.0204 | 1250 | 0.3720          | 1.5665         | -3.0805          | 0.9350             | 4.6470          | -173.1577      | -253.8766    | -0.4445         | 0.1325        |
| 0.3503        | 1.2245 | 1500 | 0.3710          | 1.5889         | -3.0515          | 0.9400             | 4.6404          | -172.8680      | -253.6525    | -0.4406         | 0.1347        |
| 0.3427        | 1.4286 | 1750 | 0.3697          | 1.5903         | -3.0719          | 0.9450             | 4.6622          | -173.0719      | -253.6384    | -0.4355         | 0.1387        |
| 0.3353        | 1.6327 | 2000 | 0.3699          | 1.5881         | -3.0875          | 0.9400             | 4.6756          | -173.2272      | -253.6602    | -0.4333         | 0.1412        |
| 0.3441        | 1.8367 | 2250 | 0.3695          | 1.5931         | -3.0842          | 0.9350             | 4.6772          | -173.1941      | -253.6105    | -0.4322         | 0.1424        |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1