---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-align-scan-6e-07-0.53-polynomial-2.0
  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. -->

# zephyr-7b-align-scan-6e-07-0.53-polynomial-2.0

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8595
- Rewards/chosen: 1.8502
- Rewards/rejected: 0.6070
- Rewards/accuracies: 0.3393
- Rewards/margins: 1.2433
- Logps/rejected: -79.9832
- Logps/chosen: -71.0003
- Logits/rejected: -2.6929
- Logits/chosen: -2.7082

## 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: 6e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7136        | 0.3484 | 100  | 0.7109          | 1.4011         | 0.8625           | 0.3512             | 0.5386          | -79.5010       | -71.8476     | -2.5458         | -2.5618       |
| 0.7461        | 0.6969 | 200  | 0.7643          | 1.0640         | 0.3687           | 0.3274             | 0.6952          | -80.4327       | -72.4838     | -2.5601         | -2.5759       |
| 0.3949        | 1.0453 | 300  | 0.7875          | 0.2070         | -0.6350          | 0.3472             | 0.8420          | -82.3265       | -74.1006     | -2.6135         | -2.6292       |
| 0.3838        | 1.3937 | 400  | 0.8714          | 0.4396         | -0.7042          | 0.3294             | 1.1438          | -82.4571       | -73.6618     | -2.6266         | -2.6422       |
| 0.371         | 1.7422 | 500  | 0.8639          | 0.6923         | -0.5434          | 0.3393             | 1.2357          | -82.1536       | -73.1851     | -2.6910         | -2.7068       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1