---
library_name: transformers
base_model: allenai/tulu-2-7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: ultrafeedback-binarized-tulu-2-7b-dpo-full
  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. -->

# ultrafeedback-binarized-tulu-2-7b-dpo-full

This model is a fine-tuned version of [allenai/tulu-2-7b](https://huggingface.co/allenai/tulu-2-7b) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6636
- Rewards/chosen: 0.0407
- Rewards/rejected: -0.0326
- Rewards/accuracies: 0.6746
- Rewards/margins: 0.0733
- Logps/rejected: -317.3561
- Logps/chosen: -335.2600
- Logits/rejected: -1.2511
- Logits/chosen: -1.1780

## 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: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6762        | 0.4184 | 100  | 0.6753          | 0.0546         | 0.0122           | 0.6627             | 0.0424          | -312.8761      | -333.8717    | -1.2638         | -1.1861       |
| 0.6604        | 0.8368 | 200  | 0.6640          | 0.0423         | -0.0311          | 0.6706             | 0.0734          | -317.2082      | -335.1042    | -1.2523         | -1.1794       |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1