---
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-7e-07-0.99-cosine-2.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-align-scan-7e-07-0.99-cosine-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: 1.1727
- Rewards/chosen: 2.6978
- Rewards/rejected: 0.6816
- Rewards/accuracies: 0.3472
- Rewards/margins: 2.0163
- Logps/rejected: -80.4399
- Logps/chosen: -71.7662
- Logits/rejected: -2.6444
- Logits/chosen: -2.6613

## 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: 7e-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: cosine
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.9118        | 0.3484 | 100  | 0.8952          | 1.8796         | 1.1355           | 0.3353             | 0.7441          | -79.9814       | -72.5926     | -2.5564         | -2.5727       |
| 0.9553        | 0.6969 | 200  | 1.0700          | 2.5989         | 1.4006           | 0.3413             | 1.1983          | -79.7136       | -71.8661     | -2.5726         | -2.5893       |
| 0.4066        | 1.0453 | 300  | 1.0729          | 2.3164         | 0.9125           | 0.3433             | 1.4038          | -80.2066       | -72.1515     | -2.5962         | -2.6126       |
| 0.3805        | 1.3937 | 400  | 1.1546          | 2.9774         | 1.1937           | 0.3373             | 1.7837          | -79.9225       | -71.4837     | -2.6247         | -2.6413       |
| 0.3975        | 1.7422 | 500  | 1.1824          | 2.5463         | 0.5342           | 0.3452             | 2.0120          | -80.5887       | -71.9193     | -2.6463         | -2.6632       |


### Framework versions

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